scholarly journals Leaf area prediction models for Zinnia elegans Jacq., Zinnia haageana regel and 'profusion cherry'

2004 ◽  
Vol 61 (1) ◽  
pp. 47-52 ◽  
Author(s):  
Ana Christina Rossini Pinto ◽  
Teresinha de Jesus Deléo Rodrigues ◽  
José Carlos Barbosa ◽  
Izabel Cristina Leite
Keyword(s):  
Developmental Stage ◽  
Leaf Area ◽  
Linear Models ◽  
Prediction Models ◽  
Nondestructive Method ◽  
Zinnia Elegans ◽  
Image Analysis System ◽  
Flower Bud ◽  
Maximum Width ◽  
Analysis System

Leaf area measurements are of value in physiological and agronomic studies. The use of prediction models to estimate leaf area is a simple, accurate and nondestructive method. The present work suggests leaf area prediction models for Zinnia elegans ('Liliput' and 'Thumbelina'), Z. haageana ('Carpet Persa') and Z. elegans x Z. angustifolia ('Profusion Cherry'), potential flower potplant cultivars. At the stages of visible apical flower bud and flowering, 250 and 300 leaves were collected from greenhouse grown plants, respectively, at each season (fall, winter, spring and summer), totaling 1,000 and 1,200 leaves, for each developmental stage. The maximum length (L), maximum width (W) and real leaf area (RLA) were measured with a Digital Image Analysis System - Delta T Devices. The relation between RLA and the product of length by width (LW), was studied through linear models, for each cultivar, at each developmental stage. The models for the flower bud stage were: RLA = 0.0009 + 0.7765 LW ('Profusion Cherry'), RLA = 0.0021 + 0.8156 LW ('Thumbelina'), RLA = 0.0031 + 0.8003 LW ('Liliput'), RLA = 0.0036 + 0.7719 LW ('Carpet Persa'), and for flowering stage: RLA = 0.0029 + 0.7899 LW ('Profusion Cherry'), RLA = 0.8318 LW ('Thumbelina'), RLA = 0.001 + 0.8417 LW ('Liliput'), RLA = 0.0042 + 0.723 LW ('Carpet Persa'). Models were considered adequate to estimate leaf area.

scholarly journals A linear model for leaf area measurement to screen potential leaf material for herbal drug in Adhatoda vasica L.

2016 ◽  
Vol 8 (1) ◽  
pp. 140-143
Author(s):  
J. V. Thaker ◽  
R. P. Kuvad ◽  
V. S. Thaker
Keyword(s):  
Water Content ◽  
Leaf Area ◽  
Linear Model ◽  
Plant Species ◽  
Linear Models ◽  
Dry Weight ◽  
Nondestructive Method ◽  
Area Measurement ◽  
Adhatoda Vasica ◽  
Linear Correlations

Leaf area is an important parameter in physiology and agronomy studies. Linear models for leaf area measurement are developed for plant species as a nondestructive method. The plant Adhatoda vasica L. (a medicinal plant) was selected and the leaves of this plant were used for development of linear model for leaf area using Leaf Area Meter (LAM) software. Planimetric parameters (length, length2, width and width2) and gravimetric (dry weight and water content) parameters are considered for the development of linear model for this plant species. Single factor ANOVA and linear correlations were worked out using these parameters and leaf area. The plant was showed significant relationship with the parameters studied. The best correlation as represented by regression coefficient (R2) was used and improved R2 is worked out. It is observed that with increase in leaf area, water content is also increased and showed best correlation with the leaf area. Thus water content can be taken as a parameter for developing linear model for leaf area is concluded.

scholarly journals Regression models for prediction of leaf area in purple ipe [Tabebuia impetiginosa (Mart.)]

2020 ◽  
pp. 654-659
Author(s):  
Jéssica Sayuri Hassuda Santos ◽  
Karina Tiemi Hassuda dos Santos ◽  
Vinicius de Souza Oliveira ◽  
Gleyce Pereira Santos ◽  
Luis Fernando Tavares de Menezes ◽  
...  
Keyword(s):  
Leaf Area ◽  
Regression Models ◽  
Linear Models ◽  
Regression Equations ◽  
Linear Quadratic ◽  
Maximum Width ◽  
Quadratic Potential ◽  
Area Estimate ◽  
Non Destructive

Besides its medicinal and ornamental use, Tabebuia impetiginosa is also very economically important. The achievement of accurate and easy-to-perform tools to determine its leaf area is fundamental for understanding the interaction between the plant and the environment. The objective of this work was to obtain regression equations by using several models that use allometric measurements of the fifth leaflet and to select the most accurate one to determine the leaf area of composite leaves of Tabebuia impetiginosa Mart. in a non-destructive way. By using the dimensions of the fifth leaflet such as - length (LFL in cm), maximum width (WFL in cm) and the product between LFL and WFL (LWFL) of leaf limb, the equations were estimated for linear, quadratic, potential and exponential linear models. The results showed that the determination of leaf area could be performed with excellent precision for leaves of different sizes of this species, using the product of the measurements of length and width of the fifth leaflet. The equation that best expresses the leaf area estimate of the composite leaf of Tabebuia impetiginosa is ELACL = 8.7772 + 2.3840 (LWFL).

Digital Processing of STEM Images

1981 ◽  
Vol 39 ◽  
pp. 236-237
Author(s):  
A. V. Crewe ◽  
M. Ohtsuki
Keyword(s):  
High Resolution ◽  
Low Dose ◽  
Assembly Language ◽  
Processing System ◽  
Principal Component ◽  
Digital Processing ◽  
Image Analysis System ◽  
Black And White ◽  
Analysis System ◽  
Dose Imaging

We have assembled an image processing system for use with our high resolution STEM for the particular purpose of working with low dose images of biological specimens. The system is quite flexible, however, and can be used for a wide variety of images.The original images are stored on magnetic tape at the microscope using the digitized signals from the detectors. For low dose imaging, these are “first scan” exposures using an automatic montage system. One Nova minicomputer and one tape drive are dedicated to this task.The principal component of the image analysis system is a Lexidata 3400 frame store memory. This memory is arranged in a 640 x 512 x 16 bit configuration. Images are displayed simultaneously on two high resolution monitors, one color and one black and white. Interaction with the memory is obtained using a Nova 4 (32K) computer and a trackball and switch unit provided by Lexidata.The language used is BASIC and uses a variety of assembly language Calls, some provided by Lexidata, but the majority written by students (D. Kopf and N. Townes).

Chemical Classification and Particle Sizing of Foundry Sands

1985 ◽  
Vol 43 ◽  
pp. 388-389
Author(s):  
D.S. DeMiglio
Keyword(s):  
Image Analysis ◽  
Energy Dispersive Spectrometer ◽  
Image Analysis System ◽  
Representative Sampling ◽  
Foundry Sands ◽  
Large Atomic Number ◽  
Backscattered Electron ◽  
Sand Particles ◽  
Analysis System ◽  
Reclamation System

Much progress has been made in recent years towards the development of closed-loop foundry sand reclamation systems. However, virtually all work to date has determined the effectiveness of these systems to remove surface clay and metal oxide scales by a qualitative inspection of a representative sampling of sand particles. In this investigation, particles from a series of foundry sands were sized and chemically classified by a Lemont image analysis system (which was interfaced with an SEM and an X-ray energy dispersive spectrometer) in order to statistically document the effectiveness of a reclamation system developed by The Pangborn Company - a subsidiary of SOHIO.The following samples were submitted: unreclaimed sand; calcined sand; calcined & mechanically scrubbed sand and unused sand. Prior to analysis, each sample was sprinkled onto a carbon mount and coated with an evaporated film of carbon. A backscattered electron photomicrograph of a field of scale-covered particles is shown in Figure 1. Due to a large atomic number difference between sand particles and the carbon mount, the backscattered electron signal was used for image analysis since it had a uniform contrast over the shape of each particle.

Цифровая морфометрия разнокачественности семян овощных культур

2018 ◽  
Author(s):  
F.B. Musaev ◽  
N.S. Priyatkin ◽  
M.V. Arkhipov ◽  
P.A. Shchukina ◽  
A.F. Bukharov ◽  
...  
Keyword(s):  
Seed Quality ◽  
Image Analysis System ◽  
Flatbed Scanner ◽  
The Future ◽  
Scanned Images ◽  
Computer Morphometry ◽  
Analysis System ◽  
Matrix Heterogeneity ◽  
Relationship Of ◽  
Selection Of

Приведено описание разработанной авторами методики цифровой компьютерной морфометрии семян овощных культур на основе системы анализа изображений, состоящей из планшетного сканера и программного обеспечения для автоматических измерений. В основу метода положено представление о разнокачественности семян, обусловленной генетической неоднородностью самих семенных растений, используемых в промышленном семеноводстве. Физические свойства семян (их форма и линейные размеры) – основные параметры при определении их качества. Цифровые изображения семян получены при помощи планшетного сканера HP Sсanjet 200 на базе Агрофизического НИИ с использованием серийного программного обеспечения «Argus-BIO», производства ООО «АргусСофт» (г. Санкт-Петербург). Метод состоит из подбора контрастной подложки (фона) для сканирования семян с минимальными теневыми эффектами, калибровку программного обеспечения для привязки к истинным размерным величинам, подбор параметров измерений и автоматическое распознавание цифровых сканированных изображений семян. Представлены экспериментальные данные по морфометрии экологически разнокачественных семян фасоли овощной, матрикально разнокачественных семян укропа, пастернака и лука Кристофа. Семена укропа и пастернака, собранные из разных порядков ветвления семенного растения, значительно различались по величине линейных параметров. Наиболее показательный линейный параметр семян – площадь проекции. Предложенная авторами методика цифровой морфометрии, уже использована на практике и в перспективе может быть задействована в исследованиях экологической и матрикальной разнокачественности семян овощных культур. Так, она прошла апробацию на разнокачественных семенах пяти сортов фасоли овощной (Настена, Магура, Миробела, Морена, Бажена) полученных в пяти контрастных эколого-географических условиях среды (Москва, Белгород, Ставрополь, Омск, Горки) в 2011–2012 годах. В дальнейшем методика может быть использована для улучшения качества цифровых изображений семян, изучения разнокачественности семян в том числе и для совершенствования контроля за селекционным процессом. Кроме того, она применима для изучения взаимосвязи совокупности морфометрических характеристик семян и их посевных качеств.The description of the method of digital computer morphometry of vegetable seeds developed by the authors on the basis of the image analysis system consisting of a flatbed scanner and software for automatic measurements is given. The method is based on the idea of seed quality, due to the genetic heterogeneity of the seed plants used in industrial seed production. Physical properties of seeds (their shape and linear dimensions) are the main parameters in determining their quality. Digital image of the seed obtained using the flatbed scanner, HP Sсanjet 200 on the basis of the Agrophysical research Institute with serial software “Argus-BIO”, produced by LLC “Argussoft” (Saint-Petersburg). The method consists of selection of a contrast substrate (background) for scanning seeds with minimal shadow effects, calibration of software for binding to true size values, selection of measurement parameters and automatic recognition of digital scanned images of seeds. Experimental data on the morphometry of ecologically different-quality seeds of vegetable beans, matrix seeds of dill, Pasternak and Christoph onion are presented. Seeds of dill and parsnip, collected from different orders of branching of the seed plant, significantly differed in size of linear parameters. The most revealing linear parameter seed – area projection. The method of digital morphometry proposed by the authors has already been used in practice and in the future can be used in studies of ecological and matrix heterogeneity of vegetable seeds. So, it was tested on different quality seeds of five varieties of vegetable beans (Nastena, Magura, Mirobelа, Morena, Bazhenf) obtained in five contrasting environmental and geographical conditions (Moscow, Belgorod, Stavropol, Omsk, Gorki) in 2011-2012. In the future, the technique can be used to improve the quality of digital images of seeds, study of seed diversity, including to improve the control of the breeding process. In addition, it is applicable to study the relationship of the set of morphometric characteristics of seeds and their sowing qualities.

Sign in / Sign up

Export Citation Format

Share Document