Leaf rust (caused by Puccinia triticina Erikss. [Pt]) is increasingly impacting durum wheat (Triticum turgidum L. var. durum) production with the recent appearance of races with virulence to widely grown cultivars in many durum producing areas worldwide. A highly virulent P. triticina race on durum wheat was recently detected in Kansas. This race may spread to the northern Great Plains, where most of the US durum wheat is produced. The objective of this study was to identify sources of resistance to several races from the United States and Mexico at seedling stage in the greenhouse and at adult stage in field experiments. Genome-wide association study (GWAS) was used to identify single-nucleotide polymorphism (SNP) markers associated with leaf rust response in a worldwide durum wheat collection of 496 accessions. Thirteen accessions were resistant across all experiments. Association mapping revealed 88 significant SNPs associated with leaf rust response. Of these, 33 SNPs were located on chromosomes 2A and 2B, and 55 SNPs were distributed across all other chromosomes except for 1B and 7B. Twenty markers were associated with leaf rust response at seedling stage, while 68 markers were associated with leaf rust response at adult plant stage. The current study identified a total of 14 previously uncharacterized loci associated with leaf rust response in durum wheat. The discovery of these loci through association mapping (AM) is a significant step in identifying useful sources of resistance that can be used to broaden the relatively narrow leaf rust resistance spectrum in durum wheat germplasm. Abbreviations: AM, association mapping; ARS, Agricultural Research Service; CDL, Cereal Disease Laboratory; GWAS, genome-wide association study; IT, infection type; LD, linkage disequilibrium; MAF, minor allele frequency; MR, moderately resistant; MS, moderately susceptible; MSD, mean squared difference; NSGC, National Small Grain Collection; PC, principal component; PCA, principal component analysis; pFDR, positive false discovery rate; Pt, Puccinia triticina Erikss.; QTL, quantitative trait loci; R, resistant; S, susceptible; SNP, single-nucleotide polymorphism; SSR, simple-sequence repeat. Core Ideas• Thirteen durum wheat accessions showed resistance to all Puccinia triticina races tested• GWAS revealed 88 SNPs (37 loci) associated with leaf rust response in durum wheat• Associations were identified on all chromosomes except 1B and 7B• GWAS revealed 14 previously uncharacterized loci for leaf rust resistance

Breeding for grain yield, biotic and abiotic stress resistance, and end-use quality are important goals of wheat breeding programs. Screening for end-use quality traits is usually secondary to grain yield due to high labor needs, cost of testing, and large seed requirements for phenotyping. Genomic selection provides an alternative to predict performance using genome-wide markers under forward and across location predictions, where a previous year’s dataset can be used to build the models. Due to large datasets in breeding programs, we explored the potential of the machine and deep learning models to predict fourteen end-use quality traits in a winter wheat breeding program. The population used consisted of 666 wheat genotypes screened for five years (2015–19) at two locations (Pullman and Lind, WA, USA). Nine different models, including two machine learning (random forest and support vector machine) and two deep learning models (convolutional neural network and multilayer perceptron) were explored for cross-validation, forward, and across locations predictions. The prediction accuracies for different traits varied from 0.45–0.81, 0.29–0.55, and 0.27–0.50 under cross-validation, forward, and across location predictions. In general, forward prediction accuracies kept increasing over time due to increments in training data size and was more evident for machine and deep learning models. Deep learning models were superior over the traditional ridge regression best linear unbiased prediction (RRBLUP) and Bayesian models under all prediction scenarios. The high accuracy observed for end-use quality traits in this study support predicting them in early generations, leading to the advancement of superior genotypes to more extensive grain yield trails. Furthermore, the superior performance of machine and deep learning models strengthens the idea to include them in large scale breeding programs for predicting complex traits.

Leaf rust caused by Puccinia triticina Erikss. ( Pt ) and stem rust caused by Puccinia graminis f. sp. tritic i Erikss. & E. Henn ( Pgt ) are serious constraints to production of durum wheat ( Triticum turgidum L). The objective of this study was to identify leaf rust resistance ( Lr ) and stem rust resistance ( Sr ) genes/QTL in Portuguese durum landrace PI 192051. Four Pt -isolates, representing three virulence phenotypes (BBBQJ, BBBSJ & EEEEE) and six Pgt -races TTKSK, JRCQC, TKTTF, QFCFC, TPMKC and TMLKC were used to evaluate 180 recombinant inbred lines (RILs) derived from the cross Rusty (rust susceptible) × PI 192051-1 (rust resistant) at the seedling stage. The RILs were also phenotyped at the adult-plant stage in a stem rust nursery in Ethiopia in 2017. The RILs were genotyped using the Illumina iSelect 9K wheat SNP array. PI 192051-1 carries a previously unidentified major Sr gene designated as QSr.ace-7A on chromosome arm 7AS and Lr gene Lr.ace-4A in the pericentromeric region of chromosome 4A. In addition, three minor Sr QTL QSr.ace-1A , QSr.ace-2B and QSr.ace-4A were mapped in PI 192051-1 on chromosomes 1AL, 2BL, and 4A, respectively Lr.ace-4A could be co-located or tightly linked to QSr.ace-4A . Markers linked to the identified QTL/genes can be used for marker assisted selection. These findings enrich the genetic basis of rust resistance in both durum and common wheat.

The widespread contamination of foods by mycotoxins continues to be a public health hazard in sub-Saharan Africa, with maize and groundnut being major sources of contamination. This study was undertaken to assess the hypothesis that grain sorting can be used to reduce mycotoxin contamination in grain lots by removing toxic kernels. We tested a set of sorting principles and methods for reducing mycotoxin levels in maize and groundnut from a variety of genotypes and environments. We found that kernel bulk density (KBD) and 100-kernel weight (HKW) were associated with the levels of aflatoxins (AF) and fumonisins (FUM) in maize grain. A low-cost sorter prototype (the ‘DropSort’ device) that separated maize grain based on KBD and HKW was more effective in reducing FUM than AF. We then evaluated the effectiveness of DropSorting when combined with either size or visual sorting. Size sorting followed by DropSorting was the fastest method for reducing FUM to under 2 ppm, but was not effective in reducing AF levels in maize grain to under 20 ppb, especially for heavily AF-contaminated grain. Analysis of individual kernels showed that high -AF maize kernels had lower weight, volume, density, length, and width and higher sphericity than those with low AF. Single kernel weight was the most significant predictor of AF concentration. The DropSort excluded kernels with lower single kernel weight, volume, width, depth, and sphericity. We also found that visual sorting and bright greenish-yellow fluorescence sorting of maize single kernels were successful in separating kernels based on AF levels. For groundnut, the DropSort grouped grain based on HKW and did not significantly reduce AF concentrations, whereas size sorting and visual sorting were much more effective.

The Plant Genome T he world's human population is projected to reach over nine billion by 2050, which demands more food production to ensure food security by that time (Tucker et al., 2017). Wheat is a major food crop contributing about 20% of calories to the human population worldwide, and an increase in wheat production is imperative to address this challenge. Although overall genetic and genomic improvement in wheat is essential to significantly increase wheat production, development of wheat cultivars that are resistant to diverse plant diseases is also important. Among the major diseases of wheat, rust diseases, which include LR, stripe rust, and stem rust,

Durum wheat [ Triticum durum (Desf).] is mostly used to produce pasta, couscous, and bulgur. The quality of the grain and end-use products determine its market value. However, quality tests are highly resource intensive and almost impossible to conduct in the early generations in the breeding program. Modern genomics-based tools provide an excellent opportunity to genetically dissect complex quality traits to expedite cultivar development using molecular breeding approaches. This study used a panel of 243 cultivars and advanced breeding lines developed during the last 20 years to identify SNPs associated with 24 traits related to nutritional value and quality. Genome-wide association study (GWAS) identified a total of 179 marker–trait associations (MTAs), located in 95 genomic regions belonging to all 14 durum wheat chromosomes. Major and stable QTLs were identified for gluten strength on chromosomes 1A and 1B, and for PPO activity on chromosomes 1A, 2B, 3A, and 3B. As a large amount of unbalance phenotypic data are generated every year on advanced lines in all the breeding programs, the applicability of such a dataset for identification of MTAs remains unclear. We observed that ∼84% of the MTAs identified using a historic unbalanced dataset (belonging to a total of 80 environments collected over a period of 16 years) were also identified in a balanced dataset. This suggests the suitability of historic unbalanced phenotypic data to identify beneficial MTAs to facilitate local-knowledge-based breeding. In addition to providing extensive knowledge about the genetics of quality traits, association mapping identified several candidate markers to assist durum wheat quality improvement through molecular breeding. The molecular markers associated with important traits could be extremely useful in the development of improved quality durum wheat cultivars using marker-assisted selection (MAS).

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Leaf rust, caused by Puccinia triticina, and stem rust, caused by P. graminis f. sp. tritici, are important diseases of durum wheat. This study determined the inheritance and genomic locations of leaf rust resistance (Lr) genes to P. triticina race BBBQJ and stem rust resistance (Sr) genes to P. graminis f. sp. tritici race TTKSK in durum accessions. Eight leaf-rust-resistant genotypes were used to develop biparental populations. Accessions PI 192051 and PI 534304 were also resistant to P. graminis f. sp. tritici race TTKSK. The resulting progenies were phenotyped for leaf rust and stem rust response at seedling stage. The Lr and Sr genes were mapped in five populations using single-nucleotide polymorphisms and bulked segregant analysis. Five leaf-rust-resistant genotypes carried single dominant Lr genes whereas, in the remaining accessions, there was deviation from the expected segregation ratio of a single dominant Lr gene. Seven genotypes carried Lr genes different from those previously characterized in durum. The single dominant Lr genes in PI 209274, PI 244061, PI387263, and PI 313096 were mapped to chromosome arms 6BS, 2BS, 6BL, and 6BS, respectively. The Sr gene in PI 534304 mapped to 6AL and is most likely Sr13, while the Sr gene in PI 192051 could be uncharacterized in durum.