RESUMEN
Understanding the complex interactions between genotype-environment dynamics is fundamental for optimizing crop improvement. However, traditional phenotyping methods limit assessments to the end of the growing season, restricting continuous crop monitoring. To address this limitation, we developed a methodology for spatiotemporal registration of time-series 3D point cloud data, enabling field phenotyping over time for accurate crop growth tracking. Leveraging multi-scan terrestrial laser scanning (TLS), we captured high-resolution 3D LiDAR data in a cotton breeding field across various stages of the growing season to generate four-dimensional (4D) crop models, seamlessly integrating spatial and temporal dimensions. Our registration procedure involved an initial pairwise terrain-based matching for rough alignment, followed by a bird's-eye view adjustment for fine registration. Point clouds collected throughout nine sessions across the growing season were successfully registered both spatially and temporally, with average registration errors of approximately 3 cm. We used the generated 4D models to monitor canopy height (CH) and volume (CV) for eleven cotton genotypes over two months. The consistent height reference established via our spatiotemporal registration process enabled precise estimations of CH (R 2 = 0.95, RMSE = 7.6 cm). Additionally, we analyzed the relationship between CV and the interception of photosynthetically active radiation (IPAR f ), finding that it followed a curve with exponential saturation, consistent with theoretical models, with a standard error of regression (SER) of 11%. In addition, we compared mathematical models from the Richards family of sigmoid curves for crop growth modeling, finding that the logistic model effectively captured CH and CV evolution, aiding in identifying significant genotype differences. Our novel TLS-based digital phenotyping methodology enhances precision and efficiency in field phenotyping over time, advancing plant phenomics and empowering efficient decision-making for crop improvement efforts.
RESUMEN
In this study, we investigated the potential involvement of endogenous viral elements (EVEs) in the development of apical tissue necrosis, resulting in the terminal abortion of upland cotton (Gossypium hirsutum L.) in Georgia. The high-throughput sequence analysis of symptomatic and asymptomatic plant tissue samples revealed near-complete EVE-Georgia (EVE-GA) sequences closely related to caulimoviruses. The analysis of EVE-GA's putative open reading frames (ORFs) compared to cotton virus A and endogenous cotton pararetroviral elements (eCPRVE) revealed their similarity in putative ORFs 1-4. However, in the ORF 5 and ORF 6 encoding putative coat protein and reverse transcriptase, respectively, the sequences from EVE-GA have stop codons similar to eCPRVE sequences from Mississippi. In silico mining of the cotton genome database using EVE-GA as a query uncovered near-complete viral sequence insertions in the genomes of G. hirsutum species (~7 kb) but partial in G. tomentosum (~5.3 kb) and G. mustelinum (~5.1 kb) species. Furthermore, cotton EVEs' episomal forms and messenger RNA (mRNA) transcripts were detected in both symptomatic and asymptomatic plants collected from cotton fields. No significant yield difference was observed between symptomatic and asymptomatic plants of the two varieties evaluated in the experimental plot. Additionally, EVEs were also detected in cotton seeds and seedlings. This study emphasizes the need for future research on EVE sequences, their coding capacity, and any potential role in host immunity or pathogenicity.
Asunto(s)
Gossypium , Sistemas de Lectura Abierta , Enfermedades de las Plantas , Gossypium/virología , Enfermedades de las Plantas/virología , Georgia , Filogenia , Secuenciación de Nucleótidos de Alto RendimientoRESUMEN
Water deficit stress limits net photosynthetic rate (AN), but the relative sensitivities of underlying processes such as thylakoid reactions, ATP production, carbon fixation reactions, and carbon loss processes to water deficit stress in field-grown upland cotton require further exploration. Therefore, the objective of the present study was to assess (1) the diffusional and biochemical mechanisms associated with water deficit-induced declines in AN and (2) associations between water deficit-induced variation in oxidative stress and energy dissipation for field-grown cotton. Water deficit stress was imposed for three weeks during the peak bloom stage of cotton development, causing significant reductions in leaf water potential and AN. Among diffusional limitations, mesophyll conductance was the major contributor to the AN decline. Several biochemical processes were adversely impacted by water deficit. Among these, electron transport rate and RuBP regeneration were most sensitive to AN-limiting water deficit. Carbon loss processes (photorespiration and dark respiration) were less sensitive than carbon assimilation, contributing to the water deficit-induced declines in AN. Increased energy dissipation via non-photochemical quenching or maintenance of electron flux to photorespiration prevented oxidative stress. Declines in AN were not associated with water deficit-induced variation in ATP production. It was concluded that diffusional limitations followed by biochemical limitations (ETR and RuBP regeneration) contributed to declines in AN, carbon loss processes partially contributed to the decline in AN, and increased energy dissipation prevented oxidative stress under water deficit in field-grown cotton.