Read by QxMD icon Read

Plant Methods

Shuxian Li
Background: Phomopsis seed decay (PSD) of soybean ( Glycine max L. Merr.) is caused primarily by the seed-borne fungal pathogen Phomopsis longicolla T. W. Hobbs. The PSD disease reduces seed quality and yield worldwide. Development of effective techniques to evaluate soybean for resistance to PSD can facilitate identification of new sources of host resistance to manage the disease. This study was undertaken to develop and utilize a rapid cut-seedling inoculation technique to evaluate soybean genotypes for resistance to P...
2018: Plant Methods
William T Salter, Matthew E Gilbert, Thomas N Buckley
Background: Existing methods for directly measuring photosynthetic capacity ( A max ) have low throughput, which creates a key bottleneck for pre-breeding and ecological research. Currently available commercial leaf gas exchange systems are not designed to maximize throughput, on either a cost or time basis. Results: We present a novel multiplexed semi-portable gas exchange system, OCTOflux, that can measure A max with approximately 4-7 times the throughput of commercial devices, despite a lower capital cost...
2018: Plant Methods
Carmen Quiñonero López, Patricia Corral, Bénédicte Lorrain-Lorrette, Karen Martinez-Swatson, Franck Michoux, Henrik Toft Simonsen
Background: Thapsigargin and nortrilobolide are sesquiterpene lactones found in the Mediterranean plant Thapsia garganica L. Thapsigargin is a potent inhibitor of the sarco/endoplasmic reticulum calcium ATPase pump, inducing apoptosis in mammalian cells. This mechanism has been used to develop a thapsigargin-based cancer drug first by GenSpera and later Inspyr Therapeutics (Westlake Village, California). However, a stable production of thapsigargin is not established. Results: In vitro regeneration from leaf explants, shoot multiplication and rooting of T...
2018: Plant Methods
Maja Zagorščak, Andrej Blejec, Živa Ramšak, Marko Petek, Tjaša Stare, Kristina Gruden
Background: Progress in high-throughput molecular methods accompanied by more complex experimental designs demands novel data visualisation solutions. To specifically answer the question which parts of the specifical biological system are responding in particular perturbation, integrative approach in which experimental data are superimposed on a prior knowledge network is shown to be advantageous. Results: We have developed DiNAR, Differential Network Analysis in R, a user-friendly application with dynamic visualisation that integrates multiple condition high-throughput data and extensive biological prior knowledge...
2018: Plant Methods
Andrew Fletcher, Jack Christopher, Mal Hunter, Greg Rebetzke, Karine Chenu
Background: Wheat ( Triticum aestivum L.) productivity is commonly limited by the availability of water. Increasing transpiration efficiency (biomass produced per unit of water used, TE) can potentially lead to increased grain yield in water-limited environments ('more crop per drop'). Currently, the ability to screen large populations for TE is limited by slow, low-throughput and/or expensive screening procedures. Here, we propose a low-cost, low-technology, rapid, and scalable method to screen for TE...
2018: Plant Methods
Dong Li, Xue Wang, Hengbiao Zheng, Kai Zhou, Xia Yao, Yongchao Tian, Yan Zhu, Weixing Cao, Tao Cheng
Background: The visible and near infrared region has been widely used to estimate the leaf nitrogen (N) content based on the correlation of N with chlorophyll and deep absorption valleys of chlorophyll in this region. However, most absorption features related to N are located in the shortwave infrared (SWIR) region and the physical mechanism of leaf N estimation from fresh leaf reflectance spectra remains unclear. The use of SWIR region may help us reveal the underlying mechanism of casual relationships and better understand the spectral responses to N variation from fresh leaf reflectance spectra...
2018: Plant Methods
Craig B Anderson, Benjamin K Franzmayr, Soon Won Hong, Anna C Larking, Tracey C van Stijn, Rachel Tan, Roger Moraga, Marty J Faville, Andrew G Griffiths
Background: The recent development of next-generation sequencing DNA marker technologies, such as genotyping-by-sequencing (GBS), generates thousands of informative single nucleotide polymorphism markers in almost any species, regardless of genomic resources. This enables poorly resourced or "orphan" crops/species access to high-density, high-throughput marker platforms which have revolutionised population genetics studies and plant breeding. DNA quality underpins success of GBS methods as the DNA must be amenable to restriction enzyme digestion and sequencing...
2018: Plant Methods
Wei-Qing Wang, Ole Nørregaard Jensen, Ian Max Møller, Kim H Hebelstrup, Adelina Rogowska-Wrzesinska
Background: Sample preparation is a critical process for proteomic studies. Many efficient and reproducible sample preparation methods have been developed for mass spectrometry-based proteomic analysis of human and animal tissues or cells, but no attempt has been made to evaluate these protocols for plants. We here present an LC-MS/MS-based proteomics study of barley leaf aimed at optimization of methods to achieve efficient and unbiased trypsin digestion of proteins prior to LC-MS/MS based sequencing and quantification of peptides...
2018: Plant Methods
Karlah Norkunas, Robert Harding, James Dale, Benjamin Dugdale
Background: Agroinfiltration is a simple and effective method of delivering transgenes into plant cells for the rapid production of recombinant proteins and has become the preferred transient expression platform to manufacture biologics in plants. Despite its popularity, few studies have sought to improve the efficiency of agroinfiltration to further increase protein yields. This study aimed to increase agroinfiltration-based transient gene expression in Nicotiana benthamiana by improving all levels of transgenesis...
2018: Plant Methods
Christine Terryn, Gabriel Paës, Corentin Spriet
Background: Lignocellulosic biomass is a complex network of polymers making the cell walls of plants. It represents a feedstock of sustainable resources to be converted into fuels, chemicals and materials. Because of its complex architecture, lignocellulose is a recalcitrant material that necessitates some pretreatments and several types of catalysts to be transformed efficiently. In particular, enzymes degrading lignocellulose can become inactivated due to their binding to lignin through non-specific interactions, leading to a loss in catalytic efficiency of industrial processes...
2018: Plant Methods
Ezequiel Matias Lentz, Joel-Elias Kuon, Adrian Alder, Nathalie Mangel, Ima M Zainuddin, Emily Jane McCallum, Ravi Bodampalli Anjanappa, Wilhelm Gruissem, Hervé Vanderschuren
Aim: We report the construction of a Virus-Induced Gene Silencing (VIGS) vector and an agroinoculation protocol for gene silencing in cassava ( Manihot esculenta Crantz) leaves and roots. The African cassava mosaic virus isolate from Nigeria (ACMV-[NOg]), which was initially cloned in a binary vector for agroinoculation assays, was modified for application as VIGS vector. The functionality of the VIGS vector was validated in Nicotiana benthamiana and subsequently applied in wild-type and transgenic cassava plants expressing the uidA gene under the control of the CaMV 35S promoter in order to facilitate the visualization of gene silencing in root tissues...
2018: Plant Methods
Yan Gong, Bo Duan, Shenghui Fang, Renshan Zhu, Xianting Wu, Yi Ma, Yi Peng
Background: The accurate quantification of yield in rapeseed is important for evaluating the supply of vegetable oil, especially at regional scales. Methods: This study developed an approach to estimate rapeseed yield with remotely sensed canopy spectra and abundance data by spectral mixture analysis. A six-band image of the studied rapeseed plots was obtained by an unmanned aerial vehicle (UAV) system during the rapeseed flowering stage. Several widely used vegetation indices (VIs) were calculated from canopy reflectance derived from the UAV image...
2018: Plant Methods
Fu-Yuan Zhu, Mo-Xian Chen, Neng-Hui Ye, Wang-Min Qiao, Bei Gao, Wai-Ki Law, Yuan Tian, Dong Zhang, Di Zhang, Tie-Yuan Liu, Qi-Juan Hu, Yun-Ying Cao, Ze-Zhuo Su, Jianhua Zhang, Ying-Gao Liu
Background: The next-generation sequencing (NGS) technology has greatly facilitated genomic and transcriptomic studies, contributing significantly in expanding the current knowledge on genome and transcriptome. However, the continually evolving variety of sequencing platforms, protocols and analytical pipelines has led the research community to focus on cross-platform evaluation and standardization. As a NGS pioneer in China, the Beijing Genomics Institute (BGI) has announced its own NGS platform designated as BGISEQ-500, since 2016...
2018: Plant Methods
Ling-Xiang Xu, Yi-Xin Lin, Li-Hong Wang, Yuan-Chang Zhou
Background: Seed viability monitoring is very important in ex situ germplasm preservation to detect germplasm deterioration. This requires seed-, time- and labor- saving methods with high precision to assess seed germination as viability. Although the current non-invasive, rapid, sensing methods (NRSs) are time- and labor-saving, they lack the precision and simplicity which are the virtues of traditional germination. Moreover, they consume a considerable amount of seeds to adjust sensed signals to germination percentage, which disregards the seed-saving objective...
2018: Plant Methods
Victoria Ruiz-Hernández, María José Roca, Marcos Egea-Cortines, Julia Weiss
Background: Full scent profiles emitted by living tissues can be screened by using total ion chromatograms generated in full scan mode and gas chromatography-mass spectrometry technique using Headspace Sorptive Extraction. This allows the identification of specific compounds and their absolute quantification or relative abundance. Quantifications ideally should be based on calibration curves using standards for each compound. However, the unpredictable composition of Volatile Organic Compounds (VOCs) and lack of standards make this approach difficult...
2018: Plant Methods
Sarah Taghavi Namin, Mohammad Esmaeilzadeh, Mohammad Najafi, Tim B Brown, Justin O Borevitz
Background: High resolution and high throughput genotype to phenotype studies in plants are underway to accelerate breeding of climate ready crops. In the recent years, deep learning techniques and in particular Convolutional Neural Networks (CNNs), Recurrent Neural Networks and Long-Short Term Memories (LSTMs), have shown great success in visual data recognition, classification, and sequence learning tasks. More recently, CNNs have been used for plant classification and phenotyping, using individual static images of the plants...
2018: Plant Methods
Rui Wu, Miriam Lucke, Yun-Ting Jang, Wangsheng Zhu, Efthymia Symeonidi, Congmao Wang, Joffrey Fitz, Wanyan Xi, Rebecca Schwab, Detlef Weigel
Background: Our knowledge of natural genetic variation is increasing at an extremely rapid pace, affording an opportunity to come to a much richer understanding of how effects of specific genes are dependent on the genetic background. To achieve a systematic understanding of such GxG interactions, it is desirable to develop genome editing tools that can be rapidly deployed across many different genetic varieties. Results: We present an efficient CRISPR/Cas9 toolbox of super module (SM) vectors...
2018: Plant Methods
Ping Lin, Du Li, Zhiyong Zou, Yongming Chen, Shanchao Jiang
Background: The images of different flower species had small inter-class variations across different classes as well as large intra-class variations within a class. Flower classification techniques are mainly based on the features of color, shape and texture, however, the procedure always involves too many heuristics as well as manual labor to tweak parameters, which often leads to datasets with poor qualitative and quantitative measures. The current study proposed a deep architecture of convolutional neural network (CNN) for the purposes of improving the accuracy of identifying the white flowers of Fragaria  ×  ananassa from other three wild flower species of Androsace umbellata (Lour...
2018: Plant Methods
François Vasseur, Justine Bresson, George Wang, Rebecca Schwab, Detlef Weigel
Background: The model species Arabidopsis thaliana has extensive resources to investigate intraspecific trait variability and the genetic bases of ecologically relevant traits. However, the cost of equipment and software required for high-throughput phenotyping is often a bottleneck for large-scale studies, such as mutant screening or quantitative genetics analyses. Simple tools are needed for the measurement of fitness-related traits, like relative growth rate and fruit production, without investment in expensive infrastructures...
2018: Plant Methods
Hikmat Ghosson, Adrián Schwarzenberg, Frank Jamois, Jean-Claude Yvin
Background: Metabolomics based on mass spectrometry analysis are increasingly applied in diverse scientific domains, notably agronomy and plant biology, in order to understand plants' behaviors under different stress conditions. In fact, these stress conditions are able to disrupt many biosynthetic pathways that include mainly primary metabolites. Profiling and quantifying primary metabolites remain a challenging task because they are poorly retained in reverse phase columns, due to their high polarity and acid-base properties...
2018: Plant Methods
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"