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This review describes the scientific basis of a research and breeding pathway designed to boost genetic gains in wheat under drought and heat stress., Despite being the world’s most widely grown crop, research investments in wheat (Triticum aestivum and Triticum durum) fall behind those in other staple crops. Current yield gains will not meet 2050 needs, and climate stresses compound this challenge. However, there is good evidence that heat and drought resilience can be boosted through translating promising ideas into novel breeding technologies using powerful new tools in genetics and remote sensing, for example. Such technologies can also be applied to identify climate resilience traits from among the vast and largely untapped reserve of wheat genetic resources in collections worldwide. This review describes multi-pronged research opportunities at the focus of the Heat and Drought Wheat Improvement Consortium (coordinated by CIMMYT), which together create a pipeline to boost heat and drought resilience, specifically: improving crop design targets using big data approaches; developing phenomic tools for field-based screening and research; applying genomic technologies to elucidate the bases of climate resilience traits; and applying these outputs in developing next-generation breeding methods. The global impact of these outputs will be validated through the International Wheat Improvement Network, a global germplasm development and testing system that contributes key productivity traits to approximately half of the global wheat-growing area.

Wheat cultivar Shaannong 33 (SN33) has remained highly resistant to stripe rust in the field since its release in 2009. To unravel the genetic architecture of stripe rust resistance, seedlings of 161 recombinant inbred lines (RILs) from the cross Avocet S × SN33 were evaluated with two isolates (PST-Lab.1 and PST-Lab.2) of the stripe rust pathogen (Puccinia striiformis f. sp. tritici) in the greenhouse, and the RILs were evaluated in naturally or artificially inoculated field sites during two cropping seasons. The RILs and parents were genotyped with the wheat 55K single-nucleotide polymorphism array. Three genomic regions conferring seedling resistance were mapped on chromosomes 1DS, 2AS, and 3DS, and four consistent quantitative trait loci (QTL) for adult-plant resistance (APR) were detected on 1BL, 2AS, 3DL, and 6BS. The 2AS locus conferring all-stage resistance was identified as the resistant gene Yr17 located on 2NS translocation. The QTL identified on 1BL and 6BS likely correspond to Yr29 and Yr78, respectively. An APR QTL on 3DL explaining 5.8 to 12.2% of the phenotypic variation is likely to be new. Molecular marker detection assays with the 2NS segment (Yr17), Yr29, Yr78, and QYrsn.nwafu-3DL on a panel of 420 current Chinese wheat cultivars and breeding lines indicated that these genes were present in 11.4, 7.6, 14.8, and 7.4% of entries, respectively. The interactions among these genes and QTL were additive, suggesting their potential value in enhancing stripe rust resistance breeding materials as observed in the resistant parent. In addition, we also identified two leaf necrosis genes, Ne1 and Ne2; however, the F1 plants from cross Avocet S × SN33 survived, indicating that SN33 probably has another allele of Ne1 which allows seed to be harvested.

A large genomic region spanning over 300 Mb on chromosome 6A under intense artificial selection harbors multiple loci associated with favorable traits including stripe rust resistance in wheat. The development of resistance cultivars can be an optimal strategy for controlling wheat stripe rust disease. Although loci for stripe rust resistance have been identified on chromosome 6A in previous studies, it is unclear whether these loci span a common genetic interval, and few studies have attempted to analyze the haplotype changes that have accompanied wheat improvement over the period of modern breeding. In this study, we used F2:3 families and F6:7 recombinant inbred lines (RILs) derived from a cross between a resistant CIMMYT wheat accession P10090 and the susceptible landrace Mingxian 169 to improve the resolution of the QTL on chromosome 6A. The co-located QTL, designated as YrP10090, was flanked by SNP markers AX-94460938 and AX-110585473 with a genetic interval of 3.5 cM, however, corresponding to a large physical distance of over 300 Mb in RefSeq v.1.0 (positions 107.1–446.5 Mb). More than 1,300 SNP markers in this genetic region were extracted for haplotype analysis in a panel of 1,461 worldwide common wheat accessions, and three major haplotypes (Hap1, Hap2, and Hap3) were identified. The favorable haplotype Hap1 associated with stripe rust resistance exhibited a large degree of linkage disequilibrium. Selective sweep analyses were performed between different haplotype groups, revealing specific genomic regions with strong artificial selection signals. These regions harbored multiple desirable traits associated with resilience to environmental stress, different yield components, and quality characteristics. P10090 and its derivatives that carry the desirable haplotype can provide a concrete foundation for bread wheat improvement including the genomic selection.

Spot blotch (SB), caused by Bipolaris sorokiniana, is a major fungal disease of wheat in South Asia and South America. Two biparental mapping populations with 232 F2:7 progenies each were generated, with CIMMYT breeding lines CASCABEL and KATH as resistant parents and CIANO T79 as the common susceptible parent. The two populations were evaluated for field SB resistance in CIMMYT’s Agua Fria station for three consecutive cropping seasons, with artificial inoculation. Genotyping was done with the DArTseq platform and approximately 1,500 high quality and nonredundant markers were used for quantitative trait loci (QTL) mapping. In both populations, a major QTL was found on chromosome 5A in the Vrn-A1 region, explaining phenotypic variations of 13.5 to 25.9%, which turned up to be less- or nonsignificant when days to heading and plant height were used as covariates in the analysis, implying a disease escape mechanism. Another major QTL was located on chromosome 5B in CASCABEL, accounting for 8.9 to 21.4% of phenotypic variation. Minor QTL were found on 4A and 4B in CASCABEL; 1B, 4B, and 4D in KATH; and 1B, 2B, and 4B in CIANO T79. Through an analysis of QTL projection onto the IWGSC Chinese Spring reference genome, the 5B QTL in CASCABEL was mapped in the Sb2 region, delimited by the single nucleotide polymorphism marker wsnp_Ku_c50354_55979952 and the simple sequence repeat marker gwm213, with a physical distance of about 14 Mb to the Tsn1 locus.

Key message The first cytological characterization of the 2NvS segment in hexaploid wheat; complete de novo assembly and annotation of 2NvS segment; 2NvS frequency is increasing 2NvS and is associated with higher yield. Abstract The Aegilops ventricosa 2NvS translocation segment has been utilized in breeding disease-resistant wheat crops since the early 1990s. This segment is known to possess several important resistance genes against multiple wheat diseases including root knot nematode, stripe rust, leaf rust and stem rust. More recently, this segment has been associated with resistance to wheat blast, an emerging and devastating wheat disease in South America and Asia. To date, full characterization of the segment including its size, gene content and its association with grain yield is lacking. Here, we present a complete cytological and physical characterization of this agronomically important translocation in bread wheat. We de novo assembled the 2NvS segment in two wheat varieties, ‘Jagger’ and ‘CDC Stanley,’ and delineated the segment to be approximately 33 Mb. A total of 535 high-confidence genes were annotated within the 2NvS region, with > 10% belonging to the nucleotide-binding leucine-rich repeat (NLR) gene families. Identification of groups of NLR genes that are potentially N genome-specific and expressed in specific tissues can fast-track testing of candidate genes playing roles in various disease resistances. We also show the increasing frequency of 2NvS among spring and winter wheat breeding programs over two and a half decades, and the positive impact of 2NvS on wheat grain yield based on historical datasets. The significance of the 2NvS segment in wheat breeding due to resistance to multiple diseases and a positive impact on yield highlights the importance of understanding and characterizing the wheat pan-genome for better insights into molecular breeding for wheat improvement.

Fusarium head blight (FHB) and stem rust are among the most devastating diseases of wheat worldwide. Fhb1 is the most widely utilized and the only isolated gene for FHB resistance, while Sr2 is a durable stem rust resistance gene used in rust-prone areas. The two loci are closely linked on the short arm of chromosome 3B and the two genes are in repulsion phase among cultivars. With climate change and the shift in Fusarium populations, it is imperative to develop wheat cultivars resistant to both diseases. The present study was dedicated to developing wheat germplasm combining Fhb1 and Sr2 resistance alleles in the International Maize and Wheat Improvement Center (CIMMYT)’s elite cultivars’ backgrounds. Four recombinant inbred lines (RILs) in Hartog background that have the resistant Fhb1 and Sr2 alleles in coupled phase linkage were crossed with seven CIMMYT bread wheat lines, resulting in 208 lines. Molecular markers for both genes were employed in addition to the use of pseudo-black chaff (PBC) as a phenotypic marker for the selection of Sr2. At various stages of the selection process, progeny lines were assessed for FHB index, Fusarium damaged kernels (FDK), stem rust, and PBC expression as well as other diseases of interest (stripe rust and leaf spotting diseases). The 25 best lines were selected for CIMMYT’s wheat breeding program. In addition to expressing resistance to FHB, most of these 25 lines have an acceptable level of resistance to other tested diseases. These lines will be useful for wheat breeding programs worldwide and potentially speed up the resistance breeding efforts against FHB and stem rust.

Stripe or yellow rust (YR) caused by Puccinia striiformis Westend. f. sp. tritici Erikss. is a persistent biotic-stress threatening global wheat production. To broaden our understanding of the shared genetic basis of YR resistance across multi-site and multi-year evaluations, we performed a large genome-wide association study using 43,706 YR observations on 23,346 wheat lines from the International Maize and Wheat Improvement Center evaluated between 2013 and 2019 at sites in India, Kenya and Mexico, against predominant races prevalent in the countries. We identified 114 repeatable markers tagging 20 quantitative trait loci (QTL) associated with YR on ten chromosomes including 1D, 2A, 2B, 2D, 3A, 4A, 4D, 5A, 5B and 6B, among which four QTL, QYr.cim-2DL.2, QYr.cim-2AS.1, QYr.cim-2BS.2 and QYr.cim-2BS.3 were significant in more than ten datasets. Furthermore, we report YR-associated allelic fingerprints for the largest panel of wheat breeding lines (52,067 lines) till date, creating substantial opportunities for YR favorable allele enrichment using molecular markers. Overall, the markers and fingerprints reported in this study provide excellent insights into the genetic architecture of YR resistance in different geographical regions, time-periods and wheat germplasm and are a huge resource to the global wheat breeding community for accelerating YR resistance breeding efforts.

An efficient method for ceric ammonium nitrate mediated synthesis of annularly fused hexapyrrolohexaazacoronene by oxidative cyclodehydrogenation has been reported. The photophysical properties of the representative hexaazacoronene has also been described.

Stripe rust caused by Puccinia striiformis f. sp. tritici (Pst) is one of the most destructive fungal diseases of wheat worldwide. The expanding Yr26-virulent Pst race (V26) group overcomes almost all currently deployed resistance genes in China and has continued to accumulate new virulence. Investigating the genetic architecture of stripe rust resistance in common wheat is an important basis for a successful utilization of resistance in breeding programs. A panel of 410 exotic wheat germplasms was used for characterizing new stripe rust resistance loci. This panel was genotyped using high-density wheat 660K single-nucleotide polymorphism (SNP) array, and phenotypic evaluation of seedlings for stripe rust resistance was performed using multiple Pst races. Thirty-five loci conferring resistance were identified through genome-wide association mapping, and explained phenotypic variances ranged from 53 to 75%. Of these, 14 were colocated in the proximity of the known loci, including cataloged Yr genes Yr9, Yr10, Yr26, Yr33, Yr47, Yr56, Yr57, Yr64, Yr67, Yr72, and Yr81 and three temporarily designated as YrCen, YrNP63, and YrRC detected in our quantitative trait locus (QTL) mapping studies. Seven of them (Yr9, Yr10, Yr24/26, Yr81, YrCEN, YrNP63, and YrRC) were confirmed by molecular detection or genetic analysis. New loci that were identified to be different from reported Yr genes need further confirmation. Nine QTL with significantly large phenotypic effect on resistance to all tested races were considered as major loci for effective resistance. The identified loci enrich our stripe rust resistance gene pool, and the linked SNPs should be useful for marker-assisted selection in breeding programs.

An intramolecular, gold-catalyzed alkyne hydroarylation results in the formation of the core pyrroloazepinone framework of the hymenin group of oroidin alkaloids. Elaboration of the cyclic adduct via C2-azidation, bromination of the pyrrole, and deprotection set the stage for global reduction with Mo(CO)

The durum wheat lines Heller#1 and Dunkler from the International Maize and Wheat Improvement Center Global Wheat Program showed moderate and stable adult plant resistance to leaf rust under high disease pressure over field environments in northwestern Mexico. Leaf rust phenotyping was performed on two recombinant inbred line (RIL) populations derived from crosses of Heller#1 and Dunkler with the susceptible parent Atred#2, conducted under artificially induced Puccinia triticina epidemics in 2013, 2014, 2015, and 2016. The Atred#2 × Heller#1 and Atred#2 × Dunkler populations were genotyped by single nucleotide polymorphism (SNP) platforms and diversity arrays technology markers, respectively. Four leaf rust resistance quantitative trait loci were detected simultaneously in the two RIL populations: Lr46, QLr.cim-2BC, QLr.cim-5BL, and QLr.cim-6BL based on phenotypic data across all four crop seasons. They explained 11.7 to 46.8%, 7.2 to 26.1%, 8.4 to 24.1%, and 12.4 to 28.5%, respectively, of the phenotypic variation for leaf rust resistance in Atred#2 × Heller#1 and 16.3 to 56.6%, 6.7 to 15.7%, 4.1 to 10.1%, and 5.1 to 20.2% of the variation in the Atred#2 × Dunkler population. Only the resistance allele of QLr.cim-2BC was from the susceptible parent Atred#2, and resistance alleles at other loci came from the resistant parents Heller#1 and Dunkler. The SNP markers closely linked to Lr46 and QLr.cim-2BC were converted to kompetitive allele specific PCR markers for use in marker-assisted selection to improve leaf rust resistance through crosses with Heller#1 and Dunkler sources.

1,4-Diazabicyclo[2.2.2]octane (DABCO)-catalyzed [3 + 3] cycloaddition reaction of 3-alkylidene-2-oxindole and β,γ-unsaturated α-keto esters under mild reaction conditions afforded the spirocyclohexene-oxindole with excellent diastereoselectivity. The [3 + 3] annulation is found to proceed through a vinylogous Michael-aldol cascade reaction and it allows rapid access to a diverse set of highly functionalized spirocyclohexene-oxindoles. Also, a bioactivity study of the compounds on mammalian sarcoma cells has reflected cell growth inhibitory/anti-cancer properties.

A highly efficient and regioselective palladium-catalyzed annulation protocol for a series of linear and terminally substituted 1,2- and 1,3-di(heteroaryl)alkanes to the corresponding polyheterocyclic arenes is reported. Herein, intramolecular oxidative coupling involving double C(sp2)–H bond functionalization provides a feasible access to biheteroaryl systems annulated to a six-membered ring. The methodology is not restricted to six-membered annulations and was extended to the synthesis of compounds with a seven-membered ring and biheteroaryl core.

A metal-free and mild, photoinduced decarboxylative 4-position alkylation of coumarins has been reported. Photoinduced single electron transfer has been initiated by utilizing the visible-light absorptivity of Eosin Y for a reductive generation of alkyl radicals from N-(acyloxy)phthalimide esters. Depending on the nature of N-(acyloxy)phthalimide esters (primary, secondary, and tertiary carboxylic acid derived), several saturated and unsaturated C-4 alkylated coumarins were synthesized. Both control experiments and photophysical studies supported a radical based mechanism for the selective alkylation.

Wheat (Triticum aestivum L.) is the most widely grown cereal crop in the world and is staple food to half the world’s population. The current world population is expected to reach 9.8 billion people by 2050, but food production is not expected to keep pace with demand in developing countries. Significant opportunities exist for traditional grain exporters to produce and export greater amounts of wheat to fill the gap. Karnal bunt, however, is a major threat, due to its use as a non-tariff trade barrier by several wheat-importing countries. The cultivation of resistant varieties remains the most cost-effective approach to manage the disease, but in countries that are free of the disease, genetic improvement is difficult due to quarantine restrictions. Here we report a study on pre-emptive breeding designed to identify linked molecular markers, evaluate the prospects of genomic selection as a tool, and prioritise wheat genotypes suitable for use as parents. In a genome-wide association (GWAS) study, we identified six DArTseq markers significantly linked to Karnal bunt resistance, which explained between 7.6 and 29.5% of the observed phenotypic variation. The accuracy of genomic prediction was estimated to vary between 0.53 and 0.56, depending on whether it is based solely on the identified Quantitative trait loci (QTL) markers or the use of genome-wide markers. As genotypes used as parents would be required to possess good yield and phenology, further research was conducted to assess the agronomic value of Karnal bunt resistant germplasm from the International Maize and Wheat Improvement Center (CIMMYT). We identified an ideal genotype, ZVS13_385, which possessed similar agronomic attributes to the highly successful Australian wheat variety, Mace. It is phenotypically resistant to Karnal bunt infection (

The development of nutritionally enhanced wheat (Triticum aestivum L.) with higher levels of grain iron (Fe) and zinc (Zn) offers a sustainable solution to micronutrient deficiency among resource-poor wheat consumers. One hundred and ninety recombinant inbred lines (RILs) from ‘Kachu’ × ‘Zinc-Shakti’ cross were phenotyped for grain Fe and Zn concentrations and phenological and agronomically important traits at Ciudad Obregon, Mexico in the 2017–2018, 2018–2019, and 2019–2020 growing seasons and Diversity Arrays Technology (DArT) molecular marker data were used to determine genomic regions controlling grain micronutrients and agronomic traits. We identified seven new pleiotropic quantitative trait loci (QTL) for grain Zn and Fe on chromosomes 1B, 1D, 2B, 6A, and 7D. The stable pleiotropic QTL identified have expanded the diversity of QTL that could be used in breeding for wheat biofortification. Nine RILs with the best combination of pleiotropic QTL for Zn and Fe have been identified to be used in future crossing programs and to be screened in elite yield trials before releasing as biofortified varieties. In silico analysis revealed several candidate genes underlying QTL, including those belonging to the families of the transporters and kinases known to transport small peptides and minerals (thus assisting mineral uptake) and catalyzing phosphorylation processes, respectively.

Wheat blast (WB) is a destructive disease in South America and its first outbreak in Bangladesh in 2016 posed a great risk to food security of South Asian countries. A genome wide association study (GWAS) was conducted on a diverse panel of 184 wheat genotypes from South Asia and CIMMYT. Phenotyping was conducted in eight field experiments in Bolivia and Bangladesh and a greenhouse experiment in the United States. Genotypic data included 11,401 SNP markers of the Illumina Infinium 15K BeadChip and four additional STS markers on the 2NS/2AS translocation region. Accessions with stable WB resistance across experiments were identified, which were all 2NS carriers. Nevertheless, a dozen moderately resistant 2AS lines were identified, exhibiting big variation among experiments. Significant marker-trait associations (MTA) were detected on chromosomes 1BS, 2AS, 6BS, and 7BL; but only MTAs on 2AS at the 2NS/2AS translocation region were consistently significant across experiments. The resistant accessions identified in this study could be used in production in South Asian countries as a preemptive strategy to prevent WB outbreak.

Bread wheat is a major staple cereal provides more than 20% of dietary energy and protein supply to global population. However, with increasing population growth, the problem of nutritional deficiencies is increasingly affecting the health of resource people with predominantly cereal-based diet. Therefore, the development of wheat genotypes with micronutrient-dense grains along with high-yield potential is one of the major priorities of wheat biofortification program at CIMMYT. We conducted a QTL mapping study using a recombinant inbred line (RIL) population derived from a cross between a Chinese parental line with highGZnC and a Mexican commercial bread wheat cultivar Roelfs F2007 to identify QTLs that could potentially be integrated in mineral nutrient concentrations and agronomic-related traits breeding. We evaluated 200 RIL lines for mineral nutrient concentrations and agronomic-related traits over two years. A total of 60 QTLs were detected, of which 10 QTLs for GZnC, 9 for GFeC, 5 for GPC and 36 for agronomic-related traits. Moreover, a total of 55 promising candidate genes were identified from the list of associated markers for GFeC and GZnC using the recently annotated wheat genome sequence. We identified the promising genomic regions with high mineral nutrient concentrations and acceptable yield potential, which are good resource for further use in wheat biofortification breeding programs., Highlights • Rich genetic diversity for micronutrients in wheat landraces provides novel alleles. • QTLs identified for multiple traits offers breeding competitive biofortified wheat. • Genomic regions and the candidate genes identified enables marker assisted breeding.

A direct dehydrogenative cross-coupling of azoles [C(sp2)-H] with dialkyl phosphites [P(O)-H] to access 2-phosphonated azoles using Cu(I)/Cu(II) as catalyst and K2S2O8/di- tert-butylperoxide as oxidant has been achieved. A remarkable advantage over reported procedures includes that oxazoles, imidazoles, benz(ox/othi/imid)azoles, and indole are found to react under optimized reaction conditions to provide corresponding adducts in high yields. The mechanistic insight of cross-coupling was obtained by deuterium kinetic isotope effect studies.

Key message Two QTL with major effects on DON content reduction were identified on chromosomes 3BL and 3DL, with the former showing minor and the latter showing no effects on FHB resistance. Abstract Deoxynivalenol (DON) contamination in food and feed is a major concern regarding Fusarium head blight (FHB) infection in wheat. However, relatively less attention has been paid on DON compared to FHB. In this study, a FHB-susceptible cultivar ‘NASMA’ was hybridized with a FHB-resistant CIMMYT breeding line ‘IAS20*5/H567.71’ to generate 197 recombinant inbred lines. The population was phenotyped for FHB and associated traits including DON accumulation in spray-inoculated field experiments at CIMMYT-Mexico across four years. Genotyping was performed by using the Illumina Infinium 15 K Beadchip and SSR markers. QTL mapping results indicated that the field FHB resistance was mainly controlled by QTL at Rht-D1 and Vrn-A1, along with a few minor QTL. For DON content, two major QTL were identified: the first located on chromosome 3BL (R2 of 16–24%), showing minor effects on FHB, and the second was on chromosome 3DL (R2 of 10–15%), exhibiting no effect on FHB resistance. It is likely that both DON QTL are new based on comparison with previous studies. This study indicates that resistance to DON accumulation and FHB disease could involve different genes, and the utilization of the two DON QTL in breeding could be helpful in further reducing DON contamination in food and feed. Electronic supplementary material The online version of this article (10.1007/s00122-019-03362-9) contains supplementary material, which is available to authorized users.

This paper applies reflectance spectroscopy and Advanced Space borne thermal emission reflection radiometer (ASTER) data processing to delineate dolomite-hosted rock phosphate around Udaipur City, Western India, using visible-near infrared (VNIR) and short wave infrared (SWIR) bands of the ASTER sensor. A number of ASTER image spectra and field spectra (resampled to ASTER bands) of pure dolomite and rock phosphate are compared and found to be consistent in terms of the presence of absorption minima at 2.3 µm for dolomite and the absence of the same feature in the spectra of the rock-phosphate. Before attempting spectral mapping, ASTER SWIR band data are clipped using the spatial extent of host rock; which has been prepared from the reference geological map and consequently updated using VNIR-SWIR derived image enhanced products at selected part of the study areas. Two sub-pixel spectral methods namely adaptive coherence estimator (ACE) and matched filtering (MF) methods are applied to ASTER SWIR bands to delineate rock-phosphate-rich zones within dolomite. The output images of the above algorithms are integrated in a principal component (PC) image to delineate phosphate pixels. A principal component; which has similar sign of Eigen vector loading for ACE and MF abundance image is used to delineate rock phosphate within dolomite. The results are validated in the field using a qualitative colorimetric method and also by comparing image spectra of spectrally anomalous zone with the ASTER resampled laboratory spectra of rock phosphate samples. A number of sporadic but important patches of phosphate rich zones in addition to the main surface exposures of the Jhamar Kotra Mine are confirmed in the field. The proposed method is a novel application of spectral mapping of phosphate deposits in dolomitic and carbonatic rocks and present approach of ASTER data processing can be used to delineate phosphate rich zones occurring within similar geological provinces in any parts of the world.

Multiple-trait experiments with mixed phenotypes (binary, ordinal and continuous) are not rare in animal and plant breeding programs. However, there is a lack of statistical models that can exploit the correlation between traits with mixed phenotypes in order to improve prediction accuracy in the context of genomic selection (GS). For this reason, when breeders have mixed phenotypes, they usually analyze them using univariate models, and thus are not able to exploit the correlation between traits, which many times helps improve prediction accuracy. In this paper we propose applying deep learning for analyzing multiple traits with mixed phenotype data in terms of prediction accuracy. The prediction performance of multiple-trait deep learning with mixed phenotypes (MTDLMP) models was compared to the performance of univariate deep learning (UDL) models. Both models were evaluated using predictors with and without the genotype × environment (G×E) interaction term (I and WI, respectively). The metric used for evaluating prediction accuracy was Pearson’s correlation for continuous traits and the percentage of cases correctly classified (PCCC) for binary and ordinal traits. We found that a modest gain in prediction accuracy was obtained only in the continuous trait under the MTDLMP model compared to the UDL model, whereas for the other traits (1 binary and 2 ordinal) we did not find any difference between the two models. In both models we observed that the prediction performance was better for WI than for I. The MTDLMP model is a good alternative for performing simultaneous predictions of mixed phenotypes (binary, ordinal and continuous) in the context of GS.

The paper compares food and straw fodder traits in wheat lines of 6 different CIMMYT wheat trials tested across 32 environments of South Asia (India, Nepal, Bangladesh and Pakistan). Experiments were conducted in the main spring wheat season with sowing time of mid-November to mid-December and harvest between March to April. Investigated and compared were grain yield (GY), straw yield (SY), straw nitrogen (N) content, neutral (NDF) and acid (ADF) detergent fiber, acid detergent lignin (ADL), and in vitro organic matter digestibility (IVOMD). Highly significant (P 60%), considerable (45%) for HI and straw N (40%), moderate for ADL (18%), and minor for NDF, ADF, and IVOMD ( Across all cultivar types only ADF was significantly (P 0.05) relationships were observed between N, ADF and IVOMD and SY. Among cultivars consistent relationships were only observed between N and GY which were significantly (P = 0.03 to 0.009) inversely correlated in five out of the six cultivar types. Within cultivars types ADF varied by at least 2.3% units in HTNM and 1st DRYT and up to 4.9% units in ESWYT. By extrapolation such cultivar-dependent differences will matter at wheat straw trading.

Genomic selection (GS) models have been validated for many quantitative traits in wheat (Triticum aestivum L.) breeding. However, those models are mostly constrained within the same growing cycle and the extension of GS to the case of across cycles has been a challenge, mainly due to the low predictive accuracy resulting from two factors: reduced genetic relationships between different families and augmented environmental variances between cycles. Using the data collected from diverse field conditions at the International Wheat and Maize Improvement Center, we evaluated GS for grain yield in three elite yield trials across three wheat growing cycles. The objective of this project was to employ the secondary traits, canopy temperature, and green normalized difference vegetation index, which are closely associated with grain yield from high-throughput phenotyping platforms, to improve prediction accuracy for grain yield. The ability to predict grain yield was evaluated reciprocally across three cycles with or without secondary traits. Our results indicate that prediction accuracy increased by an average of 146% for grain yield across cycles with secondary traits. In addition, our results suggest that secondary traits phenotyped during wheat heading and early grain filling stages were optimal for enhancing the prediction accuracy for grain yield.

Fifty wheat lines targeting semi-arid locations in India and Bangladesh were investigated for grain and straw yield and straw fodder quality traits for two consecutive years at two locations in India and one in Bangladesh. Fodder traits investigated were nitrogen (N), neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL), in vitro organic matter digestibility (IVOMD), and metabolizable energy content (ME). Highly significant (P

Stripe rust is a major disease constraint of wheat production worldwide. Resistance to stripe rust was analyzed using 131 F6 recombinant inbred lines (RILs) derived from a cross between synthetic derived wheat line Soru#1 and wheat cultivar Naxos. The phenotype was evaluated in Mexico and Norway at both seedling and adult plant stages. Linkage groups were constructed based on 90K single-nucleotide polymorphism (SNP), sequence-tagged site, and simple sequence repeat markers. Two major resistance loci conferred by Soru#1 were detected and located on chromosomes 1BL and 4DS. The 1BL quantitative trait loci explained 15.8 to 40.2 and 51.1% of the phenotypic variation at adult plant and seedling stages, respectively. This locus was identified as Yr24/Yr26 based on the flanking markers and infection types. Locus 4DS was flanked by molecular markers D_GB5Y7FA02JMPQ0_238 and BS00108770_51. It explained 8.4 to 27.8 and 5.5% of stripe rust variation at the adult plant and seedling stages, respectively. The 4DS locus may correspond to known resistance gene Yr28 based on the resistance source. All RILs that combine Yr24/Yr26 and Yr28 showed significantly reduced stripe rust severity in all four environments compared with the lines with only one of the genes. SNP marker BS00108770_51 was converted into a breeder-friendly kompetitive allele-specific polymerase chain reaction marker that will be useful to accelerate Yr28 deployment in wheat breeding programs.

An efficient organocatalyzed asymmetric synthesis of 2-amino-4H-(2-furanone)-3-carbonitrile via vinylogous Michael addition of non-activated β,γ-unsaturated butenolide to 2-iminochromenes has been realized.

The first occurrence of wheat blast in 2016 threatened Bangladesh's already precarious food security situation. The Bangladesh Agricultural Research Institute (BARI), together with the International Maize and Wheat Improvement Center (CIMMYT) developed and released the wheat variety BARI Gom 33 that is resistant to wheat blast and other common diseases. The new variety provides a 5–8% yield gain over the available popular varieties, as well as being zinc enriched. This study examines the potential economic benefits of BARI Gom 33 in Bangladesh. First, applying a climate analogue model, this study identified that more than 55% of the total wheat-growing area in Bangladesh (across 45 districts) is vulnerable to wheat blast. Second, applying an ex-ante impact assessment framework, this study shows that with an assumed cumulative adoption starting from 2019–20 and increasing to 30% by 2027–28, the potential economic benefits of the newly developed wheat variety far exceeds its dissemination cost by 2029–30. Even if dissemination of the new wheat variety is limited to only the ten currently blast-affected districts, the yearly average net benefits could amount to USD 0.23–1.6 million. Based on the findings, international funder agencies are urged to support the national system in scaling out the new wheat variety and wheat research in general to ensure overall food security in Bangladesh and South Asia., Highlights • Emergence of wheat blast in Bangladesh severely threatens South Asia's food security. • CIMMYT and Bangladesh has developed the first blast resistant wheat in the world. • The blast resistant BARI Gom 33 is zinc enriched and provides 5–8% yield gain. • This study examines the economic benefits of the dissemination of BARI Gom 33. • Analysis shows that the potential economic benefit far exceeds its dissemination cost.

Wheat grain yield (GY) improvement using genomic tools is important for achieving yield breakthroughs. To dissect the genetic architecture of wheat GY potential and stress-resilience, we have designed this large-scale genome-wide association study using 100 datasets, comprising 105,000 GY observations from 55,568 wheat lines evaluated between 2003 and 2019 by the International Maize and Wheat Improvement Center and national partners. We report 801 GY-associated genotyping-by-sequencing markers significant in more than one dataset and the highest number of them were on chromosomes 2A, 6B, 6A, 5B, 1B and 7B. We then used the linkage disequilibrium (LD) between the consistently significant markers to designate 214 GY-associated LD-blocks and observed that 84.5% of the 58 GY-associated LD-blocks in severe-drought, 100% of the 48 GY-associated LD-blocks in early-heat and 85.9% of the 71 GY-associated LD-blocks in late-heat, overlapped with the GY-associated LD-blocks in the irrigated-bed planting environment, substantiating that simultaneous improvement for GY potential and stress-resilience is feasible. Furthermore, we generated the GY-associated marker profiles and analyzed the GY favorable allele frequencies for a large panel of 73,142 wheat lines, resulting in 44.5 million datapoints. Overall, the extensive resources presented in this study provide great opportunities to accelerate breeding for high-yielding and stress-resilient wheat varieties.

International audience; Twelve new azole compounds were synthesized through an ene reaction involving methylidene heterocycles and phenylmaleimide, producing four oxazoles, five thiazoles, and one pyridine derivative, and ethyl glyoxylate for an oxazole and a thiazole compound. The twelve azoles have a stereogenic center in their structure. Hence, a method to separate the enantiomeric pairs, must be provided if any further study of chemical and pharmacological importance of these compounds is to be accomplished. Six chiral stationary phases were assayed: four were based on macrocyclic glycopeptide selectors and two on linear carbohydrates, i.e., derivatized maltodextrin and amylose. The enantiomers of the entire set of new chiral azole compounds were separated using three different mobile phase elution modes: normal phase, polar organic, and reversed phase. The most effective chiral stationary phase was the MaltoShell column, which was able to separate ten of the twelve compounds in one elution mode or another. Structural similarities in the newly synthesized oxazoles provided some insights into possible chiral recognition mechanisms.

The development of high-throughput genotyping and phenotyping has provided access to many tools to accelerate plant breeding programs. Unmanned Aerial Systems (UAS)-based remote sensing is being broadly implemented for field-based high-throughput phenotyping due to its low cost and the capacity to rapidly cover large breeding populations. The Structure-from-Motion photogrammetry processes aerial images taken from multiple perspectives over a field to an orthomosaic photo of a complete field experiment, allowing spectral or morphological trait extraction from the canopy surface for each individual field plot. However, some phenotypic information observable in each raw aerial image seems to be lost to the orthomosaic photo, probably due to photogrammetry processes such as pixel merging and blending. To formally assess this, we introduced a set of image processing methods to extract phenotypes from orthorectified raw aerial images and compared them to the negative control of extracting the same traits from processed orthomosaic images. We predict that standard measures of accuracy in terms of the broad-sense heritability of the remote sensing spectral traits will be higher using the orthorectified photos than with the orthomosaic image. Using three case studies, we therefore compared the broad-sense heritability of phenotypes in wheat breeding nurseries including, (1) canopy temperature from thermal imaging, (2) canopy normalized difference vegetation index (NDVI), and (3) early-stage ground cover from multispectral imaging. We evaluated heritability estimates of these phenotypes extracted from multiple orthorectified aerial images via four statistical models and compared the results with heritability estimates of these phenotypes extracted from a single orthomosaic image. Our results indicate that extracting traits directly from multiple orthorectified aerial images yielded increased estimates of heritability for all three phenotypes through proper modeling, compared to estimation using traits extracted from the orthomosaic image. In summary, the image processing methods demonstrated in this study have the potential to improve the quality of the plant trait extracted from high-throughput imaging. This, in turn, can enable breeders to utilize phenomics technologies more effectively for improved selection.

Genomic breeding technologies offer new opportunities for grain yield (GY) improvement in common wheat. In this study, we have evaluated the potential of genomic selection (GS) in breeding for GY in wheat by modeling a large dataset of 48,562 GY observations from the International Maize and Wheat Improvement Center (CIMMYT), including 36 yield trials evaluated between 2012 and 2019 in ObregonObregon, Sonora, Mexico. Our key objective was to determine the value that GS can add to the current three-stage yield testing strategy at CIMMYT and we draw inferences from predictive modeling of GY using 420 different populations, environments, cycles and model combinations. First, we evaluated the potential of genomic predictions for minimizing the number of replications and lines tested within a site and year and obtained mean prediction accuracies (PAs) of 0.56, 0.5 and 0.42 in Stages 1,2 and 3 of yield testing, respectively. However, these PAs were similar to the mean pedigree-based PAs indicating that genomic relationships added no value to pedigree relationships in the yield testing stages, characterized by small family-sizes. Second, we evaluated genomic predictions for minimizing GY testing across stages/years in ObregonObregon and observed mean PAs of 0.41, 0.31 and 0.37, respectively when GY in the full irrigation bed planting (FI BP), drought stress (DS), and late-sown heat stress environments were predicted across years using genotype x environment (GxE) interaction models. Third, we evaluated genomic predictions for minimizing the number of yield testing environments and observed that in Stage 2, the FI BP, full irrigation flat planting and early-sown heat stress environments (mean PA of 0.37 + 0.12) and the reduced irrigation and DS environments (mean PA of 0.45 + 0.07) had moderate predictabilities among them. However, in both predictions across years and environments, the PAs were inconsistent across years and the GxE models had no advantage over the baseline model with environment and line effects. Overall, our results provide excellent insights into the predictability of a quantitative trait like GY and will have great important implications on the future design of GS for GY in wheat breeding programs globally.

Wheat (Triticum aestivum L.) crop health assumes unprecedented significance in being the second most important staple crop of the world. It is host to an array of fungal pathogens attacking the plant at different developmental stages and accrues various degrees of yield losses owing to these. Tilletia indica that causes Karnal bunt (KB) disease in wheat is one such fungal pathogen of high quarantine importance restricting the free global trade of wheat besides the loss of grain yield as well as quality. With global climate change, the disease appears to be shifting from its traditional areas of occurrence with reports of increased vulnerabilities of new areas across the continents. This KB vulnerability of new geographies is of serious concern because once established, the disease is extremely difficult to eradicate and no known instance of its complete eradication using any management strategy has been reported yet. The host resistance to KB is the most successful as well as preferred strategy for its mitigation and control. However, breeding of KB resistant wheat cultivars has proven to be not so easy, and the low success rate owes to the scarcity of resistance sources, extremely laborious and regulated field screening protocols delaying identification/validation of putative resistance sources, and complex quantitative nature of resistance with multiple genes conferring only partial resistance. Moreover, given a lack of comprehensive understanding of the KB disease epidemiology, host-pathogen interaction, and pathogen evolution. Here, in this review, we attempt to summarize the progress made and efforts underway toward a holistic understanding of the disease itself with a specific focus on the host-pathogen interaction between T. indica and wheat as key elements in the development of resistant germplasm. In this context, we emphasize the tools and techniques being utilized in development of KB resistant germplasm by illuminating upon the genetics concerning the host responses to the KB pathogen including a future course. As such, this article could act as a one stop information primer on this economically important and re-emerging old foe threatening to cause devastating impacts on food security and well-being of communities that rely on wheat.

We untangled key regions of the genetic architecture of grain yield (GY) in CIMMYT spring bread wheat by conducting a haplotype-based, genome-wide association study (GWAS), together with an investigation of epistatic interactions using seven large sets of elite yield trials (EYTs) consisting of a total of 6,461 advanced breeding lines. These lines were phenotyped under irrigated and stress environments in seven growing seasons (2011–2018) and genotyped with genotyping-by-sequencing markers. Genome-wide 519 haplotype blocks were constructed, using a linkage disequilibrium-based approach covering 14,036 Mb in the wheat genome. Haplotype-based GWAS identified 7, 4, 10, and 15 stable (significant in three or more EYTs) associations in irrigated (I), mild drought (MD), severe drought (SD), and heat stress (HS) testing environments, respectively. Considering all EYTs and the four testing environments together, 30 stable associations were deciphered with seven hotspots identified on chromosomes 1A, 1B, 2B, 4A, 5B, 6B, and 7B, where multiple haplotype blocks were associated with GY. Epistatic interactions contributed significantly to the genetic architecture of GY, explaining variation of 3.5–21.1%, 3.7–14.7%, 3.5–20.6%, and 4.4– 23.1% in I, MD, SD, and HS environments, respectively. Our results revealed the intricate genetic architecture of GY, controlled by both main and epistatic effects. The importance of these results for practical applications in the CIMMYT breeding program is discussed.

Rust diseases continuously threaten global wheat production: stem rust, leaf rust, and yellow rust caused by Puccinia graminis f. sp. tritici, Puccinia triticina, and Puccinia striiformis f. sp. tritici, respectively. Recent studies indicated that the average losses from all these three rusts reached up to 15.04 million tons per year, which is equivalent to an annual average loss of around US $2.9 billion per year. The major focus of Mexican and worldwide breeding programs is the release of rust resistant cultivars, as this is considered the best option for controlling rust diseases. In Mexico, the emphasis has been placed on genes that confer partial resistance in the adult plant stage and against a broad spectrum of rust races since the 1970s. In this study, a set of the first-generation tall varieties developed and released in the 1940s and 1950s, the first semi-dwarfs, and other releases in Mexico, all of which showed different levels of rust resistance have been phenotyped for the three rust diseases and genotyped. Results of the molecular marker detection indicated that Lr34, Lr46, Lr67, and Lr68 alone or in different gene combinations were present among the wheat cultivars. Flag leaf tip necrosis was present in all cultivars and most were positive for brown necrosis or Pseudo Black Chaff associated with the Sr2 stem rust resistance complex. The phenotypic responses to the different rust infections indicate the presence of additional slow rusting and race-specific resistance genes. The study reveals the association of the slow rusting genes with durable resistance to the three rusts including Ug99 in cultivars bred before the green revolution such as Frontera, Supremo 211, Chapingo 48, Yaqui 50, Kentana 52, Bajio 52, Bajio 53, Yaqui 53, Chapingo 53, Yaktana Tardio 54, and Mayo 54 and their descendants after intercrossing and recombination. These slow rusting genes are the backbone of the resistance in the current Mexican germplasm.

Untangling the genetic architecture of grain yield (GY) and yield stability is an important determining factor to optimize genomics-assisted selection strategies in wheat. We conducted in-depth investigation on the above using a large set of advanced bread wheat lines (4,302), which were genotyped with genotyping-by-sequencing markers and phenotyped under contrasting (irrigated and stress) environments. Haplotypes-based genome-wide-association study (GWAS) identified 58 associations with GY and 15 with superiority index Pi (measure of stability). Sixteen associations with GY were “environment-specific” with two on chromosomes 3B and 6B with the large effects and 8 associations were consistent across environments and trials. For Pi, 8 associations were from chromosomes 4B and 7B, indicating ‘hot spot’ regions for stability. Epistatic interactions contributed to an additional 5–9% variation on average. We further explored whether integrating consistent and robust associations identified in GWAS as fixed effects in prediction models improves prediction accuracy. For GY, the model accounting for the haplotype-based GWAS loci as fixed effects led to up to 9–10% increase in prediction accuracy, whereas for Pi this approach did not provide any advantage. This is the first report of integrating genetic architecture of GY and yield stability into prediction models in wheat.

Summary The incorporation of resistance genes into wheat commercial varieties is the ideal strategy to combat stripe or yellow rust (YR). In a search for novel resistance genes, we performed a large‐scale genomic association analysis with high‐density 660K single nucleotide polymorphism (SNP) arrays to determine the genetic components of YR resistance in 411 spring wheat lines. Following quality control, 371 972 SNPs were screened, covering over 50% of the high‐confidence annotated gene space. Nineteen stable genomic regions harbouring 292 significant SNPs were associated with adult‐plant YR resistance across nine environments. Of these, 14 SNPs were localized in the proximity of known loci widely used in breeding. Obvious candidate SNP variants were identified in certain confidence intervals, such as the cloned gene Yr18 and the major locus on chromosome 2BL, despite a large extent of linkage disequilibrium. The number of causal SNP variants was refined using an independent validation panel and consideration of the estimated functional importance of each nucleotide polymorphism. Interestingly, four natural polymorphisms causing amino acid changes in the gene TraesCS2B01G513100 that encodes a serine/threonine protein kinase (STPK) were significantly involved in YR responses. Gene expression and mutation analysis confirmed that STPK played an important role in YR resistance. PCR markers were developed to identify the favourable TraesCS2B01G513100 haplotype for marker‐assisted breeding. These results demonstrate that high‐resolution SNP‐based GWAS enables the rapid identification of putative resistance genes and can be used to improve the efficiency of marker‐assisted selection in wheat disease resistance breeding.

The title compound, C25H22N2O2Se, crystallizes in the space groupP21/cwith one molecule in the asymmetric unit. The compound was synthesized by the addition of phenylselenyl bromide to a cyanamide. The phenylselenyl portion and the cyano group, as well as the ketone functional group in the cyclohexa-2,5-dien-1-one portion of the structure, are disordered, with occupancy factors of 0.555 (14) and 0.445 (14).

Key message Genome-wide association mapping in conjunction with population sequencing map and Ensembl plants was used to identify markers/candidate genes linked to leaf rust, stripe rust and tan spot resistance in wheat. Abstract Leaf rust (LR), stripe rust (YR) and tan spot (TS) are some of the important foliar diseases in wheat (Triticum aestivum L.). To identify candidate resistance genes for these diseases in CIMMYT’s (International Maize and Wheat Improvement Center) International bread wheat screening nurseries, we used genome-wide association studies (GWAS) in conjunction with information from the population sequencing map and Ensembl plants. Wheat entries were genotyped using genotyping-by-sequencing and phenotyped in replicated trials. Using a mixed linear model, we observed that seedling resistance to LR was associated with 12 markers on chromosomes 1DS, 2AS, 2BL, 3B, 4AL, 6AS and 6AL, and seedling resistance to TS was associated with 14 markers on chromosomes 1AS, 2AL, 2BL, 3AS, 3AL, 3B, 6AS and 6AL. Seedling and adult plant resistance (APR) to YR were associated with several markers at the distal end of chromosome 2AS. In addition, YR APR was also associated with markers on chromosomes 2DL, 3B and 7DS. The potential candidate genes for these diseases included several resistance genes, receptor-like serine/threonine-protein kinases and defense-related enzymes. However, extensive LD in wheat that decays at about 5 × 107 bps, poses a huge challenge for delineating candidate gene intervals and candidates should be further mapped, functionally characterized and validated. We also explored a segment on chromosome 2AS associated with multiple disease resistance and identified seventeen disease resistance linked genes. We conclude that identifying candidate genes linked to significant markers in GWAS is feasible in wheat, thus creating opportunities for accelerating molecular breeding. Electronic supplementary material The online version of this article (10.1007/s00122-018-3086-6) contains supplementary material, which is available to authorized users.

Agronomic systems based on zero tillage and residue retention are becoming more important due to their potential for climate change adaptation through the reduction of soil erosion and improved water availability. Denser soil surface conditions and large amounts of crop residues, however, may be a constraint for early plant establishment, especially in irrigated production areas with high yield potential. Genotype by tillage interactions for yield are not well understood and it is unknown whether tillage should be an evaluation factor in breeding programs. Twenty-six CIMMYT bread ( Triticum aestivum ) and durum ( Triticum turgidum ) wheat genotypes, created between 1964 and 2009, were tested for yield and agronomic performance at CIMMYT’s experimental station near Ciudad Obregon, Mexico, over six years. Treatments included conventional and permanent raised beds with full and reduced irrigation. The objectives were to study breeding progress in distinct agronomic systems and to elucidate the importance of tillage and genotype by tillage interaction for yield and agronomic traits. Breeding progress was achieved irrespective of agronomic treatment. Tillage influenced plant growth and number of grains per m 2 in both wheat types. In bread wheat, genotype by tillage interaction was significant for yield, test weight, and growth parameters. However, no cross-over effects were detected and rank changes were small. In durum wheat, genotype by tillage interaction was only significant for plant growth. The results do not indicate the need for separate breeding programs. However, the question of a need for selection under zero tillage to increase breeding progress is yet to be answered.

Since 1984, the ‘Chilero’ spring wheat line developed by CIMMYT has proven to be highly resistant to leaf rust and stripe rust. Amid efforts to understand the basis of resistance of this line, a recombinant inbred line (RIL) population derived from a cross between Avocet and Chilero was studied. The parents and RILs were characterized in field trials for leaf rust and stripe rust in three locations in Mexico between 2012 and 2015 and genotyped with DArT-array, DArT-GBS, and SSR markers. A total of 6,168 polymorphic markers were used to construct genetic linkage maps. Inclusive composite interval mapping detected four colocated resistance loci to both rust diseases and two stripe rust resistant loci in the Avocet × Chilero population. Among these, the quantitative trait locus (QTL) on chromosome 1BL was identified as a pleotropic adult plant resistance gene Lr46/Yr29, whereas QLr.cim-5DS/QYr.cim-5DS was a newly discovered colocated resistance locus to both rust diseases in Chilero. Additionally, one new stripe rust resistance locus on chromosome 7BL was mapped in the current population. Avocet also contributed two minor colocated resistance QTLs situated on chromosomes 1DL and 4BS. The flanking SNP markers can be converted to breeder friendly Kompetitive Allele Specific PCR (KASP) markers for wheat breeding programs.

In this work, a method for producing highly reactive catalysed coke from medium and non-coking coal using low-grade iron ore fines as a catalyst through two different alternate routes, namely carbonisation in a stamp charge coke oven and carbonisation in a horizontal tube furnace was attempted. Phenolic resin and petroleum pitch were individually experimented as a binding material to get adequate strength. Effect of process parameters such as coal-to-iron ratio, briquetting load, binder quantity and coking to non-coking coal ratio on the coke properties such as reactivity and mechanical strength was investigated. The SEM and petrography analysis of catalysed coke were used to study the microstructure and its effects on reactivity.

The CIMMYT wheat breeding program aims to develop bread wheat (Triticum aestivum L.) genotypes that have superior grain yields, disease resistance and stress tolerance, along with appropriate quality to satisfy all stakeholders of the wheat value chain. Grain quality for wheat consists of a combination of many defined parameters including grain morphological characteristics, dough and final products properties, all of which are defined by the genotype, the environment and their interactions. Our current approach for improving grain quality is to study grain samples obtained under high yield potential environments with optimum management. To assess the effect of this strategy on quality under stressed environments, 54 genotypes were evaluated for two years under six environmental conditions, including drought and heat stress. Grain morphology (grain density and size), protein content and flour yield were severely affected by the environment, as drought and heat stress had a strong negative effect on all of these characteristics except protein content. Gluten quality (strength and extensibility) was defined more by the genotype, although the environmental effects and the interactions were also important, particularly for gluten extensibility. The current selection strategy for quality traits carried out under optimum conditions was found to be suitable to ensure high quality characteristics across several environments for most of the parameters with an overall positive outcome.

In genomic-enabled prediction, the task of improving the accuracy of the prediction of lines in environments is difficult because the available information is generally sparse and usually has low correlations between traits. In current genomic selection, although researchers have a large amount of information and appropriate statistical models to process it, there is still limited computing efficiency to do so. Although some statistical models are usually mathematically elegant, many of them are also computationally inefficient, and they are impractical for many traits, lines, environments, and years because they need to sample from huge normal multivariate distributions. For these reasons, this study explores two recommender systems: item-based collaborative filtering (IBCF) and the matrix factorization algorithm (MF) in the context of multiple traits and multiple environments. The IBCF and MF methods were compared with two conventional methods on simulated and real data. Results of the simulated and real data sets show that the IBCF technique was slightly better in terms of prediction accuracy than the two conventional methods and the MF method when the correlation was moderately high. The IBCF technique is very attractive because it produces good predictions when there is high correlation between items (environment–trait combinations) and its implementation is computationally feasible, which can be useful for plant breeders who deal with very large data sets.

Genomic selection (GS) facilitates the rapid selection of superior genotypes and accelerates the breeding cycle. In this review, we discuss the history, principles, and basis of GS and genomic-enabled prediction (GP) as well as the genetics and statistical complexities of GP models, including genomic genotype × environment (G × E) interactions. We also examine the accuracy of GP models and methods for two cereal crops and two legume crops based on random cross-validation. GS applied to maize breeding has shown tangible genetic gains. Based on GP results, we speculate how GS in germplasm enhancement (i.e., prebreeding) programs could accelerate the flow of genes from gene bank accessions to elite lines. Recent advances in hyperspectral image technology could be combined with GS and pedigree-assisted breeding.