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 that Pisum abyssinicum is a separate species different from P. fulvum and P. sativum within Pisum. 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 in P. abyssinicum and P. fulvum showed distinct functional enrichment, indicating the potential value of them as pea breeding resources in the future.

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.

While Liriomyza sativae (Diptera: Agromyzidae), an important invasive pest of ornamentals and vegetables has been found in China for the past two decades, few studies have focused on its genetics or route of invasive. In this study, we collected 288 L. sativae individuals across 12 provinces to explore its population genetic structure and migration patterns in China using seven microsatellites. We found relatively low levels of genetic diversity but moderate population genetic structure (0.05 < F ST < 0.15) in L. sativae from China. All populations deviated significantly from the Hardy-Weinberg equilibrium due to heterozygote deficiency. Molecular variance analysis revealed that more than 89% of variation was among samples within populations. A UPGMA dendrogram revealed that SH and GXNN populations formed one cluster separate from the other populations, which is in accordance with STRUCTURE and GENELAND analyses. A Mantel test indicated that genetic distance was not correlated to geographic distance (r = -0.0814, P = 0.7610), coupled with high levels of gene flow (M = 40.1-817.7), suggesting a possible anthropogenic influence on the spread of L. sativae in China and on the effect of hosts. The trend of asymmetrical gene flow was from southern to northern populations in general and did not exhibit a Bridgehead effect during the course of invasion, as can be seen by the low genetic diversity of southern populations.