Identifications of QTLs and Candidate Genes Associated with Pseudomonas syringae Responses in Cultivated Soybean (Glycine max) and Wild Soybean (Glycine soja).

Soybeans (Glycine max) are a key food crop, serving as a valuable source of both oil and plant-derived protein. Pseudomonas syringae pv. glycinea (Psg) is among the most aggressive and prevalent pathogens affecting soybean production, causing a form of bacterial spot disease that impacts soybean leaves and thereby reduces crop yields. In this study, 310 natural soybean varieties were screened for Psg resistance and susceptibility. The identified susceptible and resistant varieties were then used for linkage mapping, BSA-seq, and whole genome sequencing (WGS) analyses aimed at identifying key QTLs associated with Psg responses. Candidate Psg-related genes were further confirmed through WGS and qPCR analyses. Candidate gene haplotype analyses were used to explore the associations between haplotypes and soybean Psg resistance. In addition, landrace and wild soybean plants were found to exhibit a higher degree of Psg resistance as compared to cultivated soybean varieties. In total, 10 QTLs were identified using chromosome segment substitution lines derived from Suinong14 (cultivated soybean) and ZYD00006 (wild soybean). Glyma.10g230200 was found to be induced in response to Psg, with the Glyma.10g230200 haplotype corresponding to soybean disease resistance. The QTLs identified herein can be leveraged to guide the marker-assisted breeding of soybean cultivars that exhibit partial resistance to Psg. Moreover, further functional and molecular studies of Glyma.10g230200 have the potential to offer insight into the mechanistic basis for soybean Psg resistance.

Spatiotemporal three-dimensional phase unwrapping in digital speckle pattern interferometry.

We propose a hybrid spatiotemporal three-dimensional phase unwrapping algorithm for use in digital speckle pattern interferometry (DSPI). The feature of the proposed algorithm is the integration of one-dimensional temporal and two-dimensional spatial phase unwrapping algorithms. By demodulating the phase on a single reference point or multiple reference points using temporal phase unwrapping and on each separated phase map region using spatial phase unwrapping, the DSPI with the spatiotemporal three-dimensional phase unwrapping algorithm can realize the measurement of dynamic absolute displacements and the determination of abrupt phase changes which are usually caused by object discontinuities. We demonstrate that the presented algorithm can overcome the drawbacks of the traditional spatial and temporal phase unwrapping algorithms.