ABSTRACT
KEY MESSAGE: Hyperspectral features enable accurate classification of soybean seeds using linear discriminant analysis and GWAS for novel seed trait genes. Evaluating crop seed traits such as size, shape, and color is crucial for assessing seed quality and improving agricultural productivity. The introduction of the SUnSet toolbox, which employs hyperspectral sensor-derived image analysis, addresses this necessity. In a validation test involving 420 seed accessions from the Korean Soybean Core Collections, the pixel purity index algorithm identified seed- specific hyperspectral endmembers to facilitate segmentation. Various metrics extracted from ventral and lateral side images facilitated the categorization of seeds into three size groups and four shape groups. Additionally, quantitative RGB triplets representing seven seed coat colors, averaged reflectance spectra, and pigment indices were acquired. Machine learning models, trained on a dataset comprising 420 accession seeds and 199 predictors encompassing seed size, shape, and reflectance spectra, achieved accuracy rates of 95.8% for linear discriminant analysis model. Furthermore, a genome-wide association study utilizing hyperspectral features uncovered associations between seed traits and genes governing seed pigmentation and shapes. This comprehensive approach underscores the effectiveness of SUnSet in advancing precision agriculture through meticulous seed trait analysis.
Subject(s)
Glycine max , Phenotype , Seeds , Glycine max/genetics , Seeds/genetics , Seeds/anatomy & histology , Genome-Wide Association Study/methods , Hyperspectral Imaging/methods , Pigmentation/genetics , Image Processing, Computer-Assisted/methods , Algorithms , Machine LearningABSTRACT
Tiller number is an important trait associated with yield in rice. Tiller number in Korean japonica rice was analyzed under greenhouse conditions in 160 recombinant inbred lines (RILs) derived from a cross between the temperate japonica varieties Odae and Unbong40 to identify quantitative trait loci (QTLs). A genetic map comprising 239 kompetitive allele-specific PCR (KASP) and 57 cleaved amplified polymorphic sequence markers was constructed. qTN3, a major QTL for tiller number, was identified at 132.4 cm on chromosome 3. This QTL was also detected under field conditions in a backcross population; thus, qTN3 was stable across generations and environments. qTN3 co-located with QTLs associated with panicle number per plant and culm diameter, indicating it had pleiotropic effects. The qTN3 regions of Odae and Unbong40 differed in a known functional variant (4 bp TGTG insertion/deletion) in the 5' UTR of OsTB1, a gene underlying variation in tiller number and culm strength. Investigation of variation in genotype and tiller number revealed that varieties with the insertion genotype had lower tiller numbers than those with the reference genotype. A high-resolution melting marker was developed to enable efficient marker-assisted selection. The QTL qTN3 will therefore be useful in breeding programs developing japonica varieties with optimal tiller numbers for increased yield.
Subject(s)
Oryza , Humans , Oryza/genetics , Plant Breeding , Chromosome Mapping , Quantitative Trait Loci/genetics , 5' Untranslated Regions , Republic of KoreaABSTRACT
Ralstonia solanacearum is a bacterial wilt pathogen of Solanum lycopersicum. Its pathogenicity is the result of coevolution during continuous interaction with its host plants under given biotic and abiotic environments. To elucidate clues for pathogenicity of our WR-1 strain, its genome sequence was analyzed.
ABSTRACT
Ralstonia pseudosolanacearum is a member of the Ralstonia solanacearum species complex (RSSC), which is composed of three species and diverse subspecific groups. Some strains cause bacterial wilt in Solanum lycopersicum; others are beneficial for their hosts. Herein, we present the complete genome sequence of an RSSC strain, Sw698, beneficial for S. lycopersicum growth.
ABSTRACT
Ralstonia solanacearum is a notorious pathogen of bacterial wilt on Solanum lycopersicum. Most isolates from diseased tomato tissues are biovar 3, and their genomes are publicly available; however, information on biovar 4 strains is limited. Here, the complete genome sequence of R. solanacearum Bs715, a biovar 4 strain, is presented.
