Discovery of leaf region and time point related modules and genes in maize(Zea mays L.)leaves by Weighted Gene Co-expression Network analysis(WGCNA)of gene expression profiles of carbon metabolism

Maize(Zea mays L.) yield depends not only on the conversion and accumulation of carbohydrates in kernels, but also on the supply of carbohydrates by leaves. However, the carbon metabolism process in leaves can vary across different leaf regions and during the day and night. Hence, we used Weighted Gene Co-expression Network analysis(WGCNA) with the gene expression profiles of carbon metabolism to identify the modules and genes that may associate with particular regions in a leaf and time of day. There were a total of 45 samples of maize leaves that were taken from three different regions of a growing maize leaf at five time points. Robust Multi-array Average analysis was used to pre-process the raw data of GSE85963(accession number), and quality control of data was based on Pearson correlation coefficients. We obtained eight co-expression network modules. The modules with the highest significance of association with LeafRegion and TimePoint were selected. Functional enrichment and gene-gene interaction analyses were conducted to acquire the hub genes and pathways in these significant modules. These results can support the findings of similar studies by providing evidence of potential module genes and enriched pathways associated with leaf development in maize.

A physics-based approach to motion capture data processing for virtual plant modeling and simulation

Dynamic virtual plant simulation is an attractive research issue in both botany and computer graphics.Data-driven method is an efficient way for motion analysis and animation synthesis.As a widely used tool,motion capture has been used in plant motion data acquisition and analysis.The most prominent and important problem in motion capture for plants is primary data processing such as missing markers reconstruction.This paper presents a novel physics-based approach to motion capture data processing of plants.Firstly,a physics-based mechanics model is found by Lagrangian mechanics for a motion captured plant organ such as a leaf,and then its dynamic mechanical properties are analyzed and relevant model parameters are evaluated.Further,by using the physical model with evaluated parameters,we can calculate the next positions of a maker to reconstruct the missing makers in motion capture sequence.We take an example of a maize leaf and pachira leaf to examine the proposed approach,and the results show that the physics-based method is feasible and effective for plant motion data processing.

Influence of temperature and light gradient on leaf arrangement and geometry in cucumber canopies: Structural phenotyping analysis and modelling

Accurate structural phenotyping analysis is essential to understand plant architectural adaptation strategy to environment change.The aim of this study was to analyze leaf arrangement and geometry influenced by azimuthally generated light gradient;and to simulate static and heterogeneous cucumber canopies using regression equations by considering more geometric parameters.Three continuous measurements of structural organ parameters were obtained to fit the organ initiation and expansion curves.Four measurements with three density treatments were obtained to validate model accuracy.To describe leaf distribution and orientation characteristics in more detail,azimuth and elevation models were introduced into canopy structure modelling.Leaf distribution frequency was simulated based on leaf area index and solar elevation angle while leaf elevation was simulated based on leaf azimuth and acropetal phytomer number.This study provides an important basis for structural phenotyping analysis of cucumber canopy,which is essential for more accurate functional-structural modelling in the future.

LettuceGDB:The community database for lettuce genetics and omics

As a globally popular leafy vegetable and a representative plant of the Asteraceae family,lettuce has great economic and academic significance.In the last decade,high-throughput sequencing,phenotyping,and other multi-omics data in lettuce have accumulated on a large scale,thus increasing the demand for an integrative lettuce database.Here,we report the establishment of a comprehensive lettuce database,LettuceGDB(https://www.lettucegdb.com/).As an omics data hub,the current LettuceGDB includes two reference genomes with detailed annotations;re-sequencing data from over 1000 lettuce varieties;a collection of more than 1300 worldwide germplasms and millions of accompanying phenotypic records obtained with manual and cutting-edge phenomics technologies;re-analyses of 256 RNA sequencing datasets;a complete miRNAome;extensive metabolite information for representative varieties and wild relatives;epigenetic data on the genome-wide chromatin accessibility landscape;and various lettuce research papers published in the last decade.Five hierarchically accessible functions(Genome,Genotype,Germplasm,Phenotype,and O-Omics)have been developed with a user-friendly interface to enable convenient data access.Eight built-in tools(Assembly Converter,Search Gene,BLAST,JBrowse,Primer Design,Gene Annotation,Tissue Expression,Literature,and Data)are available for data downloading and browsing,functional gene exploration,and experimental practice.A community forum is also available for information sharing,and a summary of current research progress on different aspects of lettuce is included.We believe that LettuceGDB can be a comprehensive functional database amenable to data mining and database-driven exploration,useful for both scientific research and lettuce breeding.

MVS-Pheno:A Portable and Low-Cost Phenotyping Platform for Maize Shoots Using Multiview Stereo 3D Reconstruction

Plant phenotyping technologies play important roles in plant research and agriculture.Detailed phenotypes of individual plants can guide the optimization of shoot architecture for plant breeding and are useful to analyze the morphological differences in response to environments for crop cultivation.Accordingly,high-throughput phenotyping technologies for individual plants grown in field conditions are urgently needed,and MVS-Pheno,a portable and low-cost phenotyping platform for individual plants,was developed.The platform is composed of four major components:a semiautomatic multiview stereo(MVS)image acquisition device,a data acquisition console,data processing and phenotype extraction software for maize shoots,and a data management system.The platform’s device is detachable and adjustable according to the size of the target shoot.Image sequences for each maize shoot can be captured within 60-120 seconds,yielding 3D point clouds of shoots are reconstructed using MVS-based commercial software,and the phenotypic traits at the organ and individual plant levels are then extracted by the software.The correlation coefficient(R^(2))between the extracted and manually measured plant height,leaf width,and leaf area values are 0.99,0.87,and 0.93,respectively.A data management system has also been developed to store and manage the acquired raw data,reconstructed point clouds,agronomic information,and resulting phenotypic traits.The platform offers an optional solution for high-throughput phenotyping of field-grown plants,which is especially useful for large populations or experiments across many different ecological regions.

An interactive design method for realistic fruit rot modeling and simulation

This paper presents a general 3D method to simulate a rotting process in fruits using a visual model for the digital design of the fruits.The global rot parameter and rot resistance parameter are used to control a dynamic simulation of a rotting process.The rot resistance parameters of every point of a 3D fruit model are generated by an interactive designing method that is similar to the traditional sketch drawing tools.We construct a texture of a rot region on a fruit surface by resistance parameters.The degree of rot that is used to control both shape and appearance of rotten fruit surface can be computed by tuning the resistance parameters and global rot parameters.We derive an exponential function to calculate the depression displacement of geometric shape caused by the rot.In order to render a wrinkle on the rot region,we use a normal noise map to modify a normal vector of fruit model and use an isotropic ward BRDF model to represent an appearance of fruit in which the time-varying diffuse reflectance is derived from the real photos.We utilize a linear function to control the dynamic simulation processes including shape deformation and aging appearance.We have evaluated our method by simulating the rotten apple and moldy orange.The results have shown that our method provides a dynamic,real-time and realistic simulation,and it is flexible,fast and of a general character for digital fruit design as a visualization model.