scholarly journals Rapid Measurement of Physical Quality of Dry Chili – A Machine Vision Approach

2021 ◽  
Vol 2 (1) ◽  
Keyword(s):  
Machine Vision ◽  
Physical Quality ◽  
Rapid Measurement

The Utilization of Red Dragon Fruit Peel Extract (Hylocereus costaricencis) As A Natural Colorant of Dried Noodle

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Silaturahmi Silaturahmi ◽  
Zaidiyah Zaidiyah ◽  
Tengku Mia Rahmiati
Keyword(s):  
Product Diversification ◽  
Fruit Peel ◽  
Physical Quality ◽  
Natural Colorant ◽  
Randomized Design ◽  
Solid Loss ◽  
Dragon Fruit ◽  
Completely Randomized Design ◽  
Peel Extract

The use of colorants in the dried noodle manufactures is an effort of product diversification. Besides of being used as a natural coloring agent, this peel extract is also used to improve nutritional value of the expected product. The purpose of this study was to determine the effect of red dragon fruit peel extract on the physical quality of dried noodle.  The study was conducted by using Completely Randomized Design (CRD) method with one factor, namely concentration of red dragon fruit peel extract (N1 = 10 ml, N2 = 15 ml, N3 = 20 ml, N4 = 25 ml, N5 = 30 ml).  The observations of its physical quality consisted of water absorption, solid loss during cooking, and organoleptic tests (aroma and color).  The best quality of dried noodle was obtained by using 30 ml red dragon fruit peel extract (N5) with physical properties, namely DSA levels of 351.92%, solid loss during cooking 4.78%, aroma 3.79 (like) and color 3.89 (like).

scholarly journals A Machine Vision Rapid Method to Determine the Ripeness Degree of Olive Lots

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2940
Author(s):  
Luciano Ortenzi ◽  
Simone Figorilli ◽  
Corrado Costa ◽  
Federico Pallottino ◽  
Simona Violino ◽  
...  
Keyword(s):  
Machine Vision ◽  
Nearest Neighbors ◽  
Calibration Method ◽  
Mobile App ◽  
Harvest Time ◽  
Automatic Assessment ◽  
K Nearest Neighbors ◽  
Olive Ripeness ◽  
Olive Ripening

The degree of olive maturation is a very important factor to consider at harvest time, as it influences the organoleptic quality of the final product, for both oil and table use. The Jaén index, evaluated by measuring the average coloring of olive fruits (peel and pulp), is currently considered to be one of the most indicative methods to determine the olive ripening stage, but it is a slow assay and its results are not objective. The aim of this work is to identify the ripeness degree of olive lots through a real-time, repeatable, and objective machine vision method, which uses RGB image analysis based on a k-nearest neighbors classification algorithm. To overcome different lighting scenarios, pictures were subjected to an automatic colorimetric calibration method—an advanced 3D algorithm using known values. To check the performance of the automatic machine vision method, a comparison was made with two visual operator image evaluations. For 10 images, the number of black, green, and purple olives was also visually evaluated by these two operators. The accuracy of the method was 60%. The system could be easily implemented in a specific mobile app developed for the automatic assessment of olive ripeness directly in the field, for advanced georeferenced data analysis.

scholarly journals Inspection of Transparent Objects with Varying Light Scattering Using a Frangi Filter

2021 ◽  
Vol 7 (2) ◽  
pp. 27
Author(s):  
Dieter P. Gruber ◽  
Matthias Haselmann
Keyword(s):  
Light Scattering ◽  
Machine Vision ◽  
Nearest Neighbor ◽  
Production Testing ◽  
Transparent Objects ◽  
Frangi Filter ◽  
Anomaly Score ◽  
Difference Images ◽  
New Machine

This paper proposes a new machine vision method to test the quality of a semi-transparent automotive illuminant component. Difference images of Frangi filtered surface images are used to enhance defect-like image structures. In order to distinguish allowed structures from defective structures, morphological features are extracted and used for a nearest-neighbor-based anomaly score. In this way, it could be demonstrated that a segmentation of occurring defects is possible on transparent illuminant parts. The method turned out to be fast and accurate and is therefore also suited for in-production testing.

scholarly journals Self-reported use of vitamin D supplements is associated with higher physical quality of life scores in multiple sclerosis

2021 ◽  
Vol 49 ◽  
pp. 102760
Author(s):  
Steve Simpson-Yap ◽  
Pia Jelinek ◽  
Tracey Weiland ◽  
Nupur Nag ◽  
Sandra Neate ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Multiple Sclerosis ◽  
Vitamin D ◽  
Physical Quality ◽  
Vitamin D Supplements

Application of Machine Vision System in the Precision Inspection

2012 ◽  
Vol 546-547 ◽  
pp. 1382-1386
Author(s):  
Yin Xia Liu ◽  
Ping Zhou
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Machine Vision System ◽  
Technical Problems ◽  
Application Program ◽  
Precision Inspection ◽  
Machine Parts

In order to promote the application and development of machine vision, The paper introduces the components of a machine vision system、common lighting technique and machine vision process. And the key technical problems are also briefly discussed in the application. A reference idea for application program of testing the quality of the machine parts is offered.

scholarly journals Effects of vacuum packaging on the physical quality of minimally processed potatoes

2003 ◽  
Vol 3 (2) ◽  
pp. 81-88 ◽  
Author(s):  
Ada M. C. N. Rocha ◽  
Emilie C. Coulon ◽  
Alcina M. M. B. Morais
Keyword(s):  
Vacuum Packaging ◽  
Minimally Processed ◽  
Physical Quality ◽  
Processed Potatoes

Physical Quality of Turmeric Powder (Curcuma longga Linn) Result of Foam-mat Drying Method Using Microwave

2021 ◽  
pp. 57-65
Author(s):  
Dhinar Patliani ◽  
Dian Purbasari
Keyword(s):  
Grain Size ◽  
Moisture Content ◽  
Water Absorption ◽  
Bulk Density ◽  
Oil Absorption ◽  
Drying Method ◽  
Physical Quality ◽  
Average Grain Size ◽  
Two Factors

Turmeric (Curcuma longa L) in Indonesia is widely known as a herbal medicinal plant, food coloring, and food flavoring. The high water content of turmeric will shorten the storage time and the quality of the ingredients. The need for drying which is the process of removing the moisture content of the material with the aim of prolonging the shelf life. The use of the foam-mat drying method with the addition of adhesives aims to speed up the drying process and maintain the quality of a material. The result of drying turmeric obtained is turmeric powder product. This study used a completely randomized design (CRD) with two factors, namely the variation of the microwave oven power and the composition of the developer agent (ovalet). The research procedure was divided into two stages, namely the manufacture of powder and continued with the measurement of physical quality. The stages of making powder begin with the preparation of raw materials, stripping, size reduction, addition of developer, drying, then grinding. The second stage is measuring physical quality, namely fineness modulus, average grain size, powder moisture content, color, water absorption, oil absorption, and bulk density. The power variations used are 420 watts, 535 watts, and 680 watts, while the composition of the developer is 1%, 2%, and 4%. Data analysis using two-way ANOVA statistical test with two factors that affect the variation of power and composition of the developer (ovalet). FM values ​​ranged from 0.364 – 1.576, D values ​​ranged from 0.005 – 0.0012 mm, final moisture content values ​​ranged from 7.60 – 9.59%, powder moisture content values ​​ranged from 9.47 – 11.43%ww , L values ​​ranged from 61.46 – 65.96, a values ​​ranged from 13.54 – 16.05, b values ​​ranged from 48.21 – 52.42, DSA values ​​ranged from 2.78 – 3.54 ml/ g, DSM values ​​ranged from 1.22 – 1.60 ml/g, and DC values ​​ranged from 0.38 – 0.44 g/cm3. The combination treatment of drying power with developer is influenced by the drying power of the parameters, namely the value of moisture content, fineness modulus, average grain size, brightness level, redness level, yellowness level, oil absorption, water absorption, and bulk density. While the developer affects the finenes modulus, average grain size, yellowness level, and bulk density.

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