Complete and accurate reference genomes and annotations provide fundamental resources for functional genomics and crop breeding. Here we report a de novo assembly and annotation of a pea cultivar ZW6 with contig N50 of 8.98 Mb, which features a 243-fold increase in contig length and evident improvements in the continuity and quality of sequence in complex repeat regions compared with the existing one. Genome diversity of 118 cultivated and wild pea demonstrated thatPisum abyssinicumis a separate species different fromP. fulvumandP. sativumwithinPisum. Quantitative trait locus analyses uncovered two known Mendel’s genes related to stem length (Le/le) and seed shape (R/r) as well as some candidate genes for pod form studied by Mendel. A pan-genome of 116 pea accessions was constructed, and pan-genes preferred inP. abyssinicumandP. fulvumshowed distinct functional enrichment, indicating the potential value of them as pea breeding resources in the future.

Faba bean is an important legume crop because of its high‐yield potential and nutrition‐dense grains. There have been significant achievements in faba bean improvement in the last four decades, which led to the doubling of the global yield average. This study reviews the genetic diversity, the breeding methodologies, major achievement on biotic and abiotic traits, and the recent molecular approaches. The high genetic diversity among faba bean accessions has been useful for increasing yield potential of the crop. Substantial increase in yield potential can be gained through the development of cultivars in open pollinated conditions. In the past, many faba bean varieties that are tolerant to abiotic and biotic stresses were released worldwide. The average yield gains varied from 1.65% per year in Syria to 4.17% per year in Ethiopia. The recent advances in molecular technologies will be used to develop more coherent genetic maps, which would also facilitate assembling and ordering genomic scaffolds in a future genome‐sequencing effort and molecular‐breeding approach.

Background: Faba bean is an important legume crop in the world. Plant height and yield are important traits for crop improvement. The traditional plant height and yield measurement are labor intensive and time consuming. Therefore, it is essential to estimate these two parameters rapidly and efficiently. The purpose of this study was to provide an alternative way to accurately identify and evaluate faba bean germplasm and breeding materials. Results: The results showed that 80% of the maximum plant height extracted from two-dimensional red–green–blue (2D-RGB) images had the best fitting degree with the ground measured values, with the coefficient of determination (R²), root-mean-square error (RMSE), and normalized root-mean-square error (NRMSE) were 0.9915, 1.4411 cm and 5.02%, respectively. In terms of yield estimation, support vector machines (SVM) showed the best performance (R² = 0.7238, RMSE = 823.54 kg ha⁻¹, NRMSE = 18.38%), followed by random forests (RF) and decision trees (DT). Conclusion: The results of this study indicated that it is feasible to monitor the plant height of faba bean during the whole growth period based on UAV imagery. Furthermore, the machine learning algorithms can estimate the yield of faba bean reasonably with the multiple time points data of plant height.

Pea (Pisum sativum L.) is an important food legume globally, and is the plant species that J.G. Mendel used to lay the foundation of modern genetics. However, genomics resources of pea are limited comparing to other crop species. Application of marker assisted selection (MAS) in pea breeding has lagged behind many other crops. Development of a large number of novel and reliable SSR (simple sequence repeat) or microsatellite markers will help both basic and applied genomics research of this crop. The Illumina HiSeq 2500 System was used to uncover 8,899 putative SSR containing sequences, and 3,275 non-redundant primers were designed to amplify these SSRs. Among the 1,644 SSRs that were randomly selected for primer validation, 841 yielded reliable amplifications of detectable polymorphisms among 24 genotypes of cultivated pea (Pisum sativum L.) and wild relatives (P. fulvum Sm.) originated from diverse geographical locations. The dataset indicated that the allele number per locus ranged from 2 to 10, and that the polymorphism information content (PIC) ranged from 0.08 to 0.82 with an average of 0.38. These 1,644 novel SSR markers were also tested for polymorphism between genotypes G0003973 and G0005527. Finally, 33 polymorphic SSR markers were anchored on the genetic linkage map of G0003973 × G0005527 F₂ population.