scholarly journals Growth of pineapple plantlets during acclimatisation can be monitored through automated image analysis of the canopy

2020 ◽  
Vol 4 (4) ◽  
pp. 223-229
Author(s):  
Guillermo Soto ◽  
Gustavo Lorente ◽  
Jessica Mendoza ◽  
Evelio Dany Báez ◽  
Carlos Manuel Lorenzo ◽  
...  
Keyword(s):  
Image Analysis ◽  
Automated Image Analysis ◽  
Plant Phenotyping ◽  
Tropical Fruit ◽  
Planting Material ◽  
Non Destructive Evaluation ◽  
Plantlet Growth ◽  
Canopy Area ◽  
Mathematical Relationships ◽  
Non Destructive

AbstractPineapple is an economically important tropical fruit crop, but the lack of adequate planting material limits its productivity. A range of micropropagation protocols has been developed over the years to address this shortfall. Still, the final stage of micropropagation, i.e. acclimatisation, remains a challenge as pineapple plantlets grow very slowly. Several studies have been conducted focusing on this phase and attempting to improve plantlet growth and establishment, which requires tools for the non-destructive evaluation of growth during acclimatisation. This report describes the use of semi-automated and automated image analysis to quantify canopy growth of pineapple plantlets, during five months of acclimatisation. The canopy area progressively increased during acclimatisation, particularly after 90 days. Regression analyses were performed to determine the relationships between the automated image analysis and morphological indicators of growth. The mathematical relationships between estimations of the canopy area and the fresh and dry weights of intact plantlets, middle-aged leaves (D leaves) and roots showed determination coefficients (R2) between 0.84 and 0.92. We propose an appropriate tool for the simple, objective and non-destructive evaluation of pineapple plantlets growth, which can be generally applied for plant phenotyping, to reduce costs and develop streamlined pipelines for the assessment of plant growth.

scholarly journals 2D size, position and shape definition of defects by B-scan image analysis

2015 ◽  
Author(s):  
Michele Scafidi ◽  
Donatella Cerniglia ◽  
Tommaso Ingrassia
Keyword(s):  
Image Analysis ◽  
Cross Section ◽  
Automatic Inspection ◽  
Structural Components ◽  
Laser Ultrasonic ◽  
Non Destructive Evaluation ◽  
Ultrasonic Techniques ◽  
Definition Of ◽  
B Scan Images ◽  
Non Destructive

The non-destructive evaluation of defects by automatic procedures is of great importance for structural components. Thanks to the developments of the non-contact ultrasonic techniques, the automation of the inspections is gaining a progressively important role. In this work, an automatic inspection technique for the evaluation of defects by the analysis of B-scan images obtained by a laser ultrasonic system is presented. The data are extracted directly from a B-scan map obtained for a panel with internal defects, and are used to build an image of the cross section of the panel. The proposed automatic procedure allows the definition of size, position and shape of defects in panels of known thickness.

Automated Image Analysis Of Nuclear And Cytoplasmic Changes In Exfoliated Cells From Tracheas Treated With Carcinogen

1977 ◽  
Vol 35 ◽  
pp. 220-221
Author(s):  
S.F. Stinson ◽  
J.C. Lilga ◽  
M.B. Sporn
Keyword(s):  
Image Analysis ◽  
Pattern Analysis ◽  
Relative Proportion ◽  
Automated Image Analysis ◽  
Image Analyzer ◽  
Cross Sectional ◽  
Exfoliated Cells ◽  
Neoplastic Lesions ◽  
Analysis System ◽  
Morphologic Criterion

Increased nuclear size, resulting in an increase in the relative proportion of nuclear to cytoplasmic sizes, is an important morphologic criterion for the evaluation of neoplastic and pre-neoplastic cells. This paper describes investigations into the suitability of automated image analysis for quantitating changes in nuclear and cytoplasmic cross-sectional areas in exfoliated cells from tracheas treated with carcinogen.Neoplastic and pre-neoplastic lesions were induced in the tracheas of Syrian hamsters with the carcinogen N-methyl-N-nitrosourea. Cytology samples were collected intra-tracheally with a specially designed catheter (1) and stained by a modified Papanicolaou technique. Three cytology specimens were selected from animals with normal tracheas, 3 from animals with dysplastic changes, and 3 from animals with epidermoid carcinoma. One hundred randomly selected cells on each slide were analyzed with a Bausch and Lomb Pattern Analysis System automated image analyzer.

Progress In The Practical Application Of Automated Image Analysis To Tem Negatives

1977 ◽  
Vol 35 ◽  
pp. 214-217
Author(s):  
F. A. Heckman ◽  
E. Redman ◽  
J.E. Connolly
Keyword(s):  
Image Analysis ◽  
Image Quality ◽  
Exposure Time ◽  
Image Contrast ◽  
Automated Image Analysis ◽  
Practical Application ◽  
Factors Affecting ◽  
High Image Quality ◽  
Qualitative Evidence ◽  
Comprehensive Study

In our initial publication on this subject1) we reported results demonstrating that contrast is the most important factor in producing the high image quality required for reliable image analysis. We also listed the factors which enhance contrast in order of the experimentally determined magnitude of their effect. The two most powerful factors affecting image contrast attainable with sheet film are beam intensity and KV. At that time we had only qualitative evidence for the ranking of enhancing factors. Later we carried out the densitometric measurements which led to the results outlined below.Meaningful evaluations of the cause-effect relationships among the considerable number of variables in preparing EM negatives depend on doing things in a systematic way, varying only one parameter at a time. Unless otherwise noted, we adhered to the following procedure evolved during our comprehensive study:Philips EM-300; 30μ objective aperature; magnification 7000- 12000X, exposure time 1 second, anti-contamination device operating.

Interfacing of a TEM/STEM System to a Computer

1981 ◽  
Vol 39 ◽  
pp. 250-251
Author(s):  
P. Hagemann
Keyword(s):  
Image Analysis ◽  
Transmission Rate ◽  
Analytical Electron Microscopy ◽  
Signal Beam ◽  
Automated Image Analysis ◽  
Beam Deflection ◽  
External Control ◽  
Computer Input ◽  
Instrument Control ◽  
Data Acquisition And Processing

The use of computers in the analytical electron microscopy today shows three different trends (1) automated image analysis with dedicated computer systems, (2) instrument control by microprocessors and (3) data acquisition and processing e.g. X-ray or EEL Spectroscopy.While image analysis in the T.E.M. usually needs a television chain to get a sequential transmission suitable as computer input, the STEM system already has this necessary facility. For the EM400T-STEM system therefore an interface was developed, that allows external control of the beam deflection in TEM as well as the control of the STEM probe and video signal/beam brightness on the STEM screen.The interface sends and receives analogue signals so that the transmission rate is determined by the convertors in the actual computer periphery.

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