Studying the phenotypic diversity of landraces and older advanced cultivars, along with their distribution, is important for breeding and germplasm conservation. To this sense, we analyzed the phenotypic diversity and spreading of 108 durum wheat accessions, including 56 landraces (LANs), 15 Moroccan cultivars (MCs), and 37 North American cultivars (NACs), using thirteen phenotypic descriptors. The collection studied was phenotypically very diverse (Shannon-Weaver index, H'mean=0.66). Spike color (H'mean=0.95), glume hairiness and spike waxiness (H'mean=0.89), peduncle attitude (H'mean=0.82), awn color (H' mean=0.75), and spike density and grain color (H'mean= 0.73) were the most diverse traits. The results also showed that NACs (H'mean=0.78) and the LANs (H'mean=0.69) were more diverse than MCs (H'mean=0.53). Multiple correspondence analyses explained 19.31% of the total variability and demonstrated a clear distinction between genotypes of Morocco and North America and between the LANs and MCs. These results of phenotypic diversity and distribution of studied genotypes can make a major leap forward in national breeding programs and germplasm collection expeditions.
Inositol phosphate kinases (IPKs) play vital roles in the synthesis and regulation of cellular levels of inositol polyphosphates, which perform vital functions in eukaryotic cells as second messengers. Due to the vital biological roles of the inositol phosphates, the kinases involved in their synthesis have gained great attention. The IPK gene family has not been extensively studied in bread wheat (Triticum aestivum). In the present study, we reported a genome-wide identification, phylogenetic analysis and expression patterns of the IPK gene family in wheat. Gene structure, genome distribution, motif conservation, and gene ontology enrichment analysis were carried out systematically. A total of 24 inositol phosphate kinase (IPK) genes were identified in the wheat genome that belonged to 8 homoeologous groups. The TaIPK genes were distributed on chromosomes 1, 2, 3, 4, 5 and 7 in all the three sub-genomes A, B, and D. Based on phylogenetic analysis, these genes were classified into four subfamilies. The subfamilies were defined based on conserved domains, motifs, chromosome locations, and gene structures. Eight pairs of paralogous IPKs were identified based on the phylogenetic relationships among wheat IPKs. Gene ontology enrichment analysis revealed the significant role of IPK genes in different biological and molecular processes in addition to their role in inositol phosphate signaling. At different developmental stages, all the 24 TaIPKs exhibited diverse expression patterns in different tissues showing diversity in their biological functions. The current study identified and explored the properties of 24 IPK genes in the wheat genome at diverse levels, thus providing a strong foundation for researchers to understand the family of these kinases in wheat.
Pinus roxburghii (P. roxburghii) is an important ecological and industrial conifer of the Himalayas. Plant boom is incredibly impacted by way of environmental stresses, in particular high ranges of nitrogen (N) and ozone (O3). This work aims to explore how these factors affect the total protein content and chlorophyll levels of P. roxburghii. Three consortiums were inoculated with two-year-old P. roxburghii seedlings. The stresses of 100 kg N h−1 and 100 ppb O3 were applied for 1 month to study their effect on chlorophyll level and total protein content. To evaluate their potential mitigating effects, the fungal consortium presented promising outcomes for the chosen plant species. The elevated metabolic activities and photosynthesis rate were determined by improved total protein content and high chlorophyll level (p
Plant phenomics is the study of plant growth and performance using multidisciplinary approaches, including high-speed computing, computer vision, sensing, and robotics. Numerous phenotyping platforms, ranging from laboratories to growth chambers, greenhouses, and finally the field, have been established through substantial efforts devoted by the plant phenotyping community. These platforms offer opportunities to measure plant traits at different scales and automation levels, with reasonable throughput and accuracy. Different sensor technologies and data analysis pipelines have been successfully implemented in plant phenomics. However, the available phenotyping platforms are not without limitations, preventing the broader application of plant phenomics in crop breeding, vegetation monitoring, and precision agriculture. The present review summarizes recent advances in various phenotyping platforms in plant phenomics, highlights their limitations, and proposes research directions for future studies in this area.
Object detection and image segmentation are powerful computer vision techniques that have been widely used in plant phenotyping tasks, such as the identification of crop diseases/insects and the measurement/counting of organs (leaves, stems, fruits, etc.). This chapter summarizes recent object detection and image segmentation techniques and public datasets developed for plant phenotyping, discusses their current challenges, particularly focusing on model generalization capability, and offers a perspective on future approaches to make these techniques more helpful to the plant science community.
