Cell to whole-plant phenotyping: the best is yet to come

2013 ◽  
Vol 18 (8) ◽  
pp. 428-439 ◽  
Author(s):  
Stijn Dhondt ◽  
Nathalie Wuyts ◽  
Dirk Inzé
Keyword(s):  
Plant Phenotyping ◽  
Whole Plant ◽  
To Come

scholarly journals ECONOMIC ANALYSIS OF DIFFERENT HARVEST METHODS FOR FRESH MARKET COLLARD GREENS

HortScience ◽  
1993 ◽  
Vol 28 (4) ◽  
pp. 266G-267
Author(s):  
Paul W. Teague ◽  
Tina Gray Teague
Keyword(s):  
System Analysis ◽  
Ground Level ◽  
Field Trials ◽  
Economic Advantage ◽  
Fresh Market ◽  
Yield Data ◽  
Net Returns ◽  
Whole Plant ◽  
To Come ◽  
Harvest Method

spring field trials conducted over 2 years were used to determine differences in net returns using “cut” (harvested by removing the whole plant near the ground level for a one time over harvest) and “shucked” collards (harvested by removing marketable sized individual leaves using multiple harvests). 'Blue Max' transplants were set 11 March 1991 and 11 Feb 1992 in rows spaced 25.4cm apart on raised beds spaced 1m apart. Four spacing treatments were evaluated (7.62, 15.24, 22.86, and 30.48 cm between plants) in a RCB with 4 replications. Plants were harvested beginning 25 April 1991 and 28 April 1992 once (cut) or over 5 wks (shucked). Yields were higher for shucked collards spaced 15.24cm in both years, but no differences Were observed in cut collards. cut collards provided a higher 1st harvest yield. A system analysis to provide 1000 boxes (9.lkg) of collards/wk was imposed to determine the economics of harvest method. Cost differences Were considered to reflect differences in hectareage required, transplant cost for 4 densities, and a 25% higher harvest cost/box for shucked collards. The shuck harvest method provided an economic advantage over cutting of $9853 and $1671 in 1991 and 1992, respectively, where all production was assumed to come from transplanted collards. when a combination of transplanting and direct seeding was assumed, results indicate an economic advantage to cutting of $680 for the system using 1992 yield data.

Linking Genes to Shape in Plants Using Morphometrics

2020 ◽  
Vol 54 (1) ◽  
pp. 417-437
Author(s):  
Hao Xu ◽  
George W. Bassel
Keyword(s):  
Multiple Scales ◽  
Computational Simulation ◽  
Plant Phenotyping ◽  
Biological Complexity ◽  
Phenotypic Analysis ◽  
Mechanical Signals ◽  
Whole Plant ◽  
Plant Form ◽  
Morphological Phenotype ◽  
Quantitative Approaches

A transition from qualitative to quantitative descriptors of morphology has been facilitated through the growing field of morphometrics, representing the conversion of shapes and patterns into numbers. The analysis of plant form at the macromorphological scale using morphometric approaches quantifies what is commonly referred to as a phenotype. Quantitative phenotypic analysis of individuals with contrasting genotypes in turn provides a means to establish links between genes and shapes. The path from a gene to a morphological phenotype is, however, not direct, with instructive information progressing both across multiple scales of biological complexity and through nonintuitive feedback, such as mechanical signals. In this review, we explore morphometric approaches used to perform whole-plant phenotyping and quantitative approaches in capture processes in the mesoscales, which bridge the gaps between genes and shapes in plants. Quantitative frameworks involving both the computational simulation and the discretization of data into networks provide a putative path to predicting emergent shape from underlying genetic programs.

scholarly journals Fluxomics links cellular functional analyses to whole-plant phenotyping

2017 ◽  
Vol 68 (9) ◽  
pp. 2083-2098 ◽  
Author(s):  
Christophe Salon ◽  
Jean-Christophe Avice ◽  
Sophie Colombié ◽  
Martine Dieuaide-Noubhani ◽  
Karine Gallardo ◽  
...  
Keyword(s):  
Plant Phenotyping ◽  
Whole Plant ◽  
Functional Analyses

scholarly journals PocketMaize: An Android-Smartphone Application for Maize Plant Phenotyping

2021 ◽  
Vol 12 ◽  
Author(s):  
Lingbo Liu ◽  
Lejun Yu ◽  
Dan Wu ◽  
Junli Ye ◽  
Hui Feng ◽  
...  
Keyword(s):  
Plant Traits ◽  
Low Cost ◽  
Leaf Traits ◽  
Smartphone Application ◽  
Plant Phenotyping ◽  
Phenotypic Characterization ◽  
Whole Plant ◽  
Outdoor Environments ◽  
Calibration Algorithm ◽  
Trait Measurement

A low-cost portable wild phenotyping system is useful for breeders to obtain detailed phenotypic characterization to identify promising wild species. However, compared with the larger, faster, and more advanced in-laboratory phenotyping systems developed in recent years, the progress for smaller phenotyping systems, which provide fast deployment and potential for wide usage in rural and wild areas, is quite limited. In this study, we developed a portable whole-plant on-device phenotyping smartphone application running on Android that can measure up to 45 traits, including 15 plant traits, 25 leaf traits and 5 stem traits, based on images. To avoid the influence of outdoor environments, we trained a DeepLabV3+ model for segmentation. In addition, an angle calibration algorithm was also designed to reduce the error introduced by the different imaging angles. The average execution time for the analysis of a 20-million-pixel image is within 2,500 ms. The application is a portable on-device fast phenotyping platform providing methods for real-time trait measurement, which will facilitate maize phenotyping in field and benefit crop breeding in future.

scholarly journals Phenotypic Analysis of Germination Time of Individual Seeds Affected by Microenvironment and Management Factors for Cohort Research in Plant Factory

Agronomy ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 1680
Author(s):  
Eri Hayashi ◽  
Yumiko Amagai ◽  
Toru Maruo ◽  
Toyoki Kozai
Keyword(s):  
Plant Growth ◽  
Growth Process ◽  
Germination Percentage ◽  
Plant Phenotyping ◽  
Phenotypic Analysis ◽  
Germination Time ◽  
Commercial Cultivation ◽  
Whole Plant ◽  
Plant Factory ◽  
Management Factors

Plant phenotyping plays a crucial role in understanding variations in the phenotype of individual plants affected by environment, management, and genotype. Measurement of seed germination is an important phenotyping stage as germination impacts on the whole plant growth process. However, germination measurement has been limited to germination percentage of a seed population. Understanding of the germination time, from sowing to outbreak of the radicle from seed coat, at a single seed level is essential. How individual germination time and further plant growth are affected by its microenvironment and management factors remains elusive. Plant phenotype measurement system was developed to assess individual germination time of romaine lettuce (Lactuca sativa L. var. longifolia), using time-series two-dimensional camera images, and to analyze how microenvironment (volumetric water percent in seed tray, individual seed surface temperature and air temperature) and management factors (coated/uncoated seeds) affect the germination time for plant cohort research, emphasizing practicality in commercial cultivation. Germination experiments were conducted to demonstrate the performance of the system and its applicability for a whole plant growth process in a plant factory for commercial production and/or breeding. The developed phenotyping platform revealed the effects of microenvironment and management factors on germination time of individual seeds.

scholarly journals Automated Detection and Segmentation of Grain Spikes in Greenhouse Images Using Shallow and Deep Learning Neural Networks: A Comparison of Six Methods

2021 ◽  
Author(s):  
Sajid Ullah ◽  
Michael Henke ◽  
Narendra Narisetti ◽  
Jan Hejatko ◽  
Evgeny Gladilin
Keyword(s):  
Image Segmentation ◽  
Deep Learning ◽  
Image Data ◽  
Automated Analysis ◽  
Machine Learning Techniques ◽  
Superior Performance ◽  
Plant Phenotyping ◽  
Learning Techniques ◽  
Whole Plant ◽  
Comprehensive Comparison

Abstract Image-based plant phenotyping is the major approach to quantitative assessment of important plant properties. For automated analysis of a large amount of image data from high-throughput greenhouse measurements, efficient techniques for image segmentation are required. However, conventional approaches to whole plant and plant organ segmentation are hampered by high variability of plant and background illumination, and naturally occurring changes in geometry and colors of growing plants. Consequently, application of advanced machine learning techniques for automated image segmentation is required. Here, we investigate six advanced neural network (NN) methods for detection and segmentation of grain spikes in RGB images including three detection deep NNs (SSD, Faster-RCNN, YOLOv3/v4), two deep (U-Net, DeepLabv3+) and one shallow segmentation NNs. Our experimental results show superior performance of deep learning NNs that achieve in average more than 90% accuracy by detection and segmentation of wheat as well as barley and rye spikes. However, different methods demonstrate different performance on matured, emergent and occluded spikes. In addition to comprehensive comparison of six NN methods, a GUI-based tool (SpikeApp) provided with this work demonstrates the application of detection and segmentation NNs to fully automated spike phenotyping. Further improvements of evaluated NN approaches are discussed.

Investor-State Dispute Settlement under NAFTA Chapter 11: The Shape of Things to Come?

1998 ◽  
Vol 35 ◽  
pp. 263-290
Author(s):  
J. Anthony VanDuzer
Keyword(s):  
Free Trade Agreement ◽  
Dispute Settlement ◽  
Trade Agreement ◽  
Minimum Standards ◽  
The North ◽  
State Behaviour ◽  
Nafta Chapter 11 ◽  
To Come ◽  
The Right

SummaryRecently, there has been a proliferation of international agreements imposing minimum standards on states in respect of their treatment of foreign investors and allowing investors to initiate dispute settlement proceedings where a state violates these standards. Of greatest significance to Canada is Chapter 11 of the North American Free Trade Agreement, which provides both standards for state behaviour and the right to initiate binding arbitration. Since 1996, four cases have been brought under Chapter 11. This note describes the Chapter 11 process and suggests some of the issues that may arise as it is increasingly resorted to by investors.

Scanning Electron Microscopy-cuticular Lesions on the Roundworm Ascaris Suum

1970 ◽  
Vol 28 ◽  
pp. 114-115
Author(s):  
P. A. Madden ◽  
W. R. Anderson
Keyword(s):  
Electron Microscopy ◽  
Scanning Electron Microscopy ◽  
Freeze Drying ◽  
Room Temperature ◽  
Secondary Electron ◽  
Distilled Water ◽  
Freeze Dried ◽  
Silver Paint ◽  
To Come ◽  
Scanning Electron

The intestinal roundworm of swine is pinkish in color and about the diameter of a lead pencil. Adult worms, taken from parasitized swine, frequently were observed with macroscopic lesions on their cuticule. Those possessing such lesions were rinsed in distilled water, and cylindrical segments of the affected areas were removed. Some of the segments were fixed in buffered formalin before freeze-drying; others were freeze-dried immediately. Initially, specimens were quenched in liquid freon followed by immersion in liquid nitrogen. They were then placed in ampuoles in a freezer at −45C and sublimated by vacuum until dry. After the specimens appeared dry, the freezer was allowed to come to room temperature slowly while the vacuum was maintained. The dried specimens were attached to metal pegs with conductive silver paint and placed in a vacuum evaporator on a rotating tilting stage. They were then coated by evaporating an alloy of 20% palladium and 80% gold to a thickness of approximately 300 A°. The specimens were examined by secondary electron emmission in a scanning electron microscope.

The microstructure change of low-carbon electrical steels by residual aluminum

1989 ◽  
Vol 47 ◽  
pp. 286-287
Author(s):  
C.K. Hou ◽  
C.T. Hu ◽  
Sanboh Lee
Keyword(s):  
Annealing Treatment ◽  
Low Carbon ◽  
Electrical Steels ◽  
Vacuum Degassing ◽  
Spherical Inclusions ◽  
Residual Aluminum ◽  
Average Grain Size ◽  
The Matrix ◽  
Fine Size ◽  
To Come

The fully processed low-carbon electrical steels are generally fabricated through vacuum degassing to reduce the carbon level and to avoid the need for any further decarburization annealing treatment. This investigation was conducted on eighteen heats of such steels with aluminum content ranging from 0.001% to 0.011% which was believed to come from the addition of ferroalloys.The sizes of all the observed grains are less than 24 μm, and gradually decrease as the content of aluminum is increased from 0.001% to 0.007%. For steels with residual aluminum greater than 0. 007%, the average grain size becomes constant and is about 8.8 μm as shown in Fig. 1. When the aluminum is increased, the observed grains are changed from the uniformly coarse and equiaxial shape to the fine size in the region near surfaces and the elongated shape in the central region. SEM and EDAX analysis of large spherical inclusions in the matrix indicate that silicate is the majority compound when the aluminum propotion is less than 0.003%, then the content of aluminum in compound inclusion increases with that in steel.

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