Digital Image Analysis of Sweetpotato Storage Roots in Herbicide Trials

Digital image analysis (DIA) was evaluated for use in assessing size and shape attributes of sweetpotato [Ipomoea batatas (L.) Lam.] storage roots in herbicide studies. Digital image files of U.S. no. 1 storage roots were taken using a digital camera. Image analysis was performed using a publicly available software package. Eight size and shape attributes were measured and subjected to univariate and multivariate procedures. DIA revealed differences for storage root width and roundness attributes. Principal component analysis suggested that storage root length, width, and roundness best described the variability of the storage root sample. The results demonstrate the potential use of DIA in augmenting data from sweetpotato herbicide trials as well as other investigations that require information about storage root size and shape responses.

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Estimation of bodyweight from body measurements and determination of body measurements on Limousin cattle using digital image analysis

Animal Production Science ◽

10.1071/an14943 ◽

2016 ◽

Vol 56 (12) ◽

pp. 2060 ◽

Cited By ~ 3

Author(s):

Serkan Ozkaya ◽

Wojciech Neja ◽

Sylwia Krezel-Czopek ◽

Adam Oler

Keyword(s):

Image Analysis ◽

Body Length ◽

Digital Image ◽

Digital Image Analysis ◽

Digital Camera ◽

Body Measurements ◽

Analysis Software ◽

Body Area ◽

Image Analysis Software

The objective of this study was to predict bodyweight and estimate body measurements of Limousin cattle using digital image analysis (DIA). Body measurements including body length, wither height, chest depth, and hip height of cattle were determined both manually (by measurements stick) and by using DIA. Body area was determined by using DIA. The images of Limousin cattle were taken while cattle were standing in a squeeze chute by a digital camera and analysed by image analysis software to obtain body measurements of each animal. While comparing the actual and predicted body measurements, the accuracy was determined as 98% for wither height, 97% for hip height, 94% for chest depth and 90.6% for body length. Regression analysis between body area and bodyweight yielded an equation with R2 of 61.5%. The regression equation, which included all body traits, resulted in an R2 value of 88.7%. The results indicated that DIA can be used for accurate prediction of body measurements and bodyweight of Limousin cattle.

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Accuracy of body measurements using digital image analysis in female Holstein calves

Animal Production Science ◽

10.1071/an12006 ◽

2012 ◽

Vol 52 (10) ◽

pp. 917 ◽

Cited By ~ 6

Author(s):

Serkan Ozkaya

Keyword(s):

Image Analysis ◽

Body Length ◽

Digital Image ◽

Digital Image Analysis ◽

Digital Camera ◽

Body Measurements ◽

Analysis Software ◽

High Prediction ◽

Holstein Calves ◽

The Difference

The objective of this study was to determine the accuracy of body measurements (BM) in Holstein female calves using digital image analysis. BM including body length, wither height, chest depth, hip height, and hip width of calves were recorded by stick and tape measurements at birth, weaning and 24 weeks of age. Then photos of calves were taken while calves were standing in a squeeze chute by a digital camera and were analysed by image analysis software to obtain BM of each calf from the image in centimetres. After comparing the actual and predicted BM, the accuracy was determined as 71, 97 and 99% for body length, 69, 87 and 99% for wither height, 43, 98 and 99% for chest depth, 74, 99 and 99% for hip height and 53, 99 and 98% for hip width at birth, weaning and 24 weeks of age, respectively. The difference between actual and predicted BM was significant at birth (P < 0.01). Although there were numerical differences between actual and predicted BM, the differences were not significant at weaning and 24 weeks of age (P > 0.01). According to these results, the BM estimation of Holstein female calves using digital image analysis produced high prediction accuracy at weaning and 24 weeks of age, but not at birth. The data presented in this study indicate that the digital image analysis provides very close agreement and reality for prediction of BM of Holstein female calves.

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Monitoring the Restoration of a Seventeenth-Century Wooden Artwork Using Laser-Induced Fluorescence and Digital Image Analysis

Applied Spectroscopy ◽

10.1177/0003702820944505 ◽

2020 ◽

Vol 75 (1) ◽

pp. 70-80

Author(s):

María Auxiliadora Gómez-Morón ◽

Rocío Ortiz ◽

Francesco Colao ◽

Roberta Fantoni ◽

José Luis Gómez-Villa ◽

...

Keyword(s):

Image Analysis ◽

Digital Image ◽

Digital Image Analysis ◽

Principal Component ◽

Laser Induced Fluorescence ◽

Chemical Mapping ◽

Spectral Angle Mapper ◽

Panel Painting ◽

Processing Techniques ◽

Wooden Surface

The present paper is aimed at demonstrating the capabilities of digital image analysis (DIA) to support conservation of painted artwork. Laser-induced fluorescence (LIF) imaging has been usually used in the diagnosis of wall paintings. In this case, LIF is applied to the case study of a painted wooden canopy, and most successful data processing techniques are presented in the discussion of results. The Jesús del Gran Poder canopy, completed by Francisco Ruiz Gijón in 1692, is an oil panel painting on wood. Eight panels of the canopy have been study by LIF. This technique is capable of remotely acquiring hyperspectral images operating in fluorescence mode following ultraviolet laser excitation. LIF spectra combined with principal component analysis, spectral angle mapper, and DIA provide a chemical mapping of the treated wooden surface of the panels. Besides, LIF spectrum is as a fingerprint of the panels that allows stablishing differences between them. LIF imaging analysis has proven to be a very useful tool for mapping retouching work, tracking previous restorations, and detecting chemicals on the wood in order to monitor restorations.

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Polymorphism of oat kernel size and shape in several Canadian oat cultivars

Canadian Journal of Plant Science ◽

10.4141/cjps95-017 ◽

1995 ◽

Vol 75 (1) ◽

pp. 105-109 ◽

Cited By ~ 12

Author(s):

L. N. Pietrzak ◽

R. G. Fulcher

Keyword(s):

Image Analysis ◽

Digital Image ◽

Avena Sativa ◽

Digital Image Analysis ◽

Diversity Index ◽

Morphological Characteristics ◽

Kernel Size ◽

Seed Shape ◽

Size And Shape ◽

Oat Cultivars

This study used digital image analysis to quantify variation of morphological characteristics of oat kernels. Ten Canadian oat varieties grown in 1984 and 1985 at five and four locations, respectively, were examined. Statistically significant differences in polymorphism among varieties collected from the same location were observed. It appeared that the genetic diversity of all analyzed varieties is quite high, and results from a broad range of kernel sizes are evenly distributed within population. The environment has little effect on the polymorphism of seed shape. The same varieties grown in different locations appeared to have almost the same diversity index, and the aspect ratio (AR) depends primarily on the genetic structure of the population. However, the diversity index of AR for each variety calculated over all locations appeared to be almost the same. Key words: Oat, Avena sativa, digital image analysis, size and shape

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