The quest for optimal plant architecture

SCAG: A Stratified, Clustered, and Growing-Based Algorithm for Soybean Branch Angle Extraction and Ideal Plant Architecture Evaluation

Three-dimensional (3D) phenotyping is important for studying plant structure and function. Light detection and ranging (LiDAR) has gained prominence in 3D plant phenotyping due to its ability to collect 3D point clouds. However, organ-level branch detection remains challenging due to small targets, sparse points, and low signal-to-noise ratios. In addition, extracting biologically relevant angle traits is difficult. In this study, we developed a stratified, clustered, and growing-based algorithm (SCAG) for soybean branch detection and branch angle calculation from LiDAR data, which is heuristic, open-source, and expandable. SCAG achieved high branch detection accuracy (F-score = 0.77) and branch angle calculation accuracy (r = 0.84) when evaluated on 152 diverse soybean varieties. Meanwhile, the SCAG outperformed 2 other classic algorithms, the support vector machine (F-score = 0.53) and density-based methods (F-score = 0.55). Moreover, after applying the SCAG to 405 soybean varieties over 2 consecutive years, we quantified various 3D traits, including canopy width, height, stem length, and average angle. After data filtering, we identified novel heritable and repeatable traits for evaluating soybean density tolerance potential, such as the ratio of average angle to height and the ratio of average angle to stem length, which showed greater potential than the well-known ratio of canopy width to height trait. Our work demonstrates remarkable advances in 3D phenotyping and plant architecture screening. The algorithm can be applied to other crops, such as maize and tomato. Our dataset, scripts, and software are public, which can further benefit the plant science community by enhancing plant architecture characterization and ideal variety selection.

Genomics for Yield and Yield Components in Durum Wheat

In recent years, many efforts have been conducted to dissect the genetic basis of yield and yield components in durum wheat thanks to linkage mapping and genome-wide association studies. In this review, starting from the analysis of the genetic bases that regulate the expression of yield for developing new durum wheat varieties, we have highlighted how, currently, the reductionist approach, i.e., dissecting the yield into its individual components, does not seem capable of ensuring significant yield increases due to diminishing resources, land loss, and ongoing climate change. However, despite the identification of genes and/or chromosomal regions, controlling the grain yield in durum wheat is still a challenge, mainly due to the polyploidy level of this species. In the review, we underline that the next-generation sequencing (NGS) technologies coupled with improved wheat genome assembly and high-throughput genotyping platforms, as well as genome editing technology, will revolutionize plant breeding by providing a great opportunity to capture genetic variation that can be used in breeding programs. To date, genomic selection provides a valuable tool for modeling optimal allelic combinations across the whole genome that maximize the phenotypic potential of an individual under a given environment.

Genetic incorporation of genes for the optimal plant architecture in common wheat

Wheat grain yield is affected by plant height, which is the total length of spike, the uppermost internode, and other elongated internodes. In this study, a population of recombinant inbred lines generated from a cross between two advanced winter wheat breeding lines were phenotyped over four locations/years and genotyped by using markers of genotyping-by-sequencing (GBS) and Diversity Array Technology (DArT) for mapping of genes for three traits, including spike length, the uppermost internode length, and plant height. Five genomic regions or quantitative trait loci (QTLs) were associated with candidate genes for these traits. A major QTL was associated with Q5A, and two novel haplotypes of Q5A were identified, one for a single nucleotide polymorphism (SNP) at position -2,149 in promoter region and the other for copy number variation. Compared with one copy Q5A on chromosome 5A in Chinese Spring, the novel haplotype of Q5A with two copies Q5A was found to generate spikes that are extremely compacted. A major QTL was associated with allelic variation in the recessive vrn-A1 alleles involving in protein sequences, and this QTL was associated with increased uppermost internode length but not with plant height. A major QTL for plant height was associated with Rht-B1b on chromosome 4B, but its effects could be compromised by two new minor QTLs on chromosome 7. Collectively, the favorable alleles from the four loci can be used to establish the optimal plant height in wheat.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-022-01336-2.