RGB color imaging to detect Aspergillus flavus infection in dates

Teena, M.; Manickavasagan, Annamalai; Al-Sadi, Abdullah M.; Al-Yahyai, Rashid; Deadman, M. L.; Al-Ismaili, Abdulrahim M.

doi:10.9755/ejfa.2016-01-070

Cited by 5 publications

(2 citation statements)

References 15 publications

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“…With these developments, CVS has been enticing much R&D attention from the food processing industry. It has so many possibilities in itself that it can replace human vision for classification, evaluation of a different aspects of food products according to their visual appearance, and quality inspection (Koszela et al., 2017; Teena et al., 2016).…”

Section: Introductionmentioning

confidence: 99%

Study of color kinetics of banana (Musa cavendish) under microwave drying by application of image analysis

Nagvanshi

Venkata

Goswami

2020

Food sci. technol. int.

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Microwave drying works on the volumetric heating concept promoted by electromagnetic radiation at 0.915 or 2.450 GHz. In this study, banana ( Musa Cavendish) was taken as the sample and treated under microwave drying. The effect of two process variables, namely slice thickness (2, 3.5, and 5 mm) and microwave power (180 W, 360 W, and 540 W), were studied on drying kinetics and color kinetics. It was observed that the inverse variation relationship exists between drying time and microwave power level while drying time and slice thickness exhibited a direct variation relationship. A Computer Vision System (CVS) was developed to measure the color values of banana in CIELab space using an algorithm written in MATLAB software. Once the color parameters were obtained, they were fitted in First and Zero-order kinetic models. Both models were found to describe the color values adequately. This study concludes that microwave drying is a promising dehydration technique for banana drying that reduces the significant time of drying. Application of CVS is an excellent approach to measure the surface color of banana.

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Section: Introductionmentioning

confidence: 99%

Study of color kinetics of banana (Musa cavendish) under microwave drying by application of image analysis

Nagvanshi

Venkata

Goswami

2020

Food sci. technol. int.

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“…RGB imaging is progressively replacing human vision in the evaluation of food quality [29] because it provides the investigator with new tools of higher quality to reliably analyze the commodity’s shape, intensity of colors of several plant structures including seeds [13]. Furthermore, these methods are relatively easy and inexpensive [19,31], particularly when used with statistics [32]. According to Wiwart, et al [13], this technique can be effectively used to effectively evaluate grains and assess DON content through the frequency of Fusarium damaged kernels (although in their study they detected RGB values and then converted them to HSI (hue, saturation, intensity), perhaps because they were more concerned with those variables).…”

Section: Rgb Imaging In Plant Pathologymentioning

confidence: 99%

Why RGB Imaging Should be Used to Analyze Fusarium Graminearum Growth and Estimate Deoxynivalenol Contamination

Cambaza

Koseki

Kawamura

2019

MPs

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Size-based fungal growth studies are limited because they do not provide information about the mold’s state of maturity, and measurements such as radius and diameter are not practical if the fungus grows irregularly. Furthermore, the current methods used to detect diseases such as Fusarium head blight (FHB) or mycotoxin contamination are labor-intensive and time consuming. FHB is frequently detected through visual examination and the results can be subjective, depending on the skills and experience of the analyzer. For toxin determination (e.g., deoxynivalenol (DON), the best methods are expensive, not practical for routine. RGB (red, green and blue) imaging analysis is a viable alternative that is inexpensive, easy to use and seemingly better if enhanced with statistical methods. This short communication explains why RGB imaging analysis should be used instead of size-based variables as a tool to measure growth of Fusarium graminearum and DON concentration.

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Near infrared imaging to detect Aspergillus flavus infection in three varieties of dates

Teena

Manickavasagan

Al-Sadi

et al. 2018

Engineering in Agriculture, Environment and Food

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RGB color imaging to detect Aspergillus flavus infection in dates

Cited by 5 publications

References 15 publications

Study of color kinetics of banana (Musa cavendish) under microwave drying by application of image analysis

Study of color kinetics of banana (Musa cavendish) under microwave drying by application of image analysis

Why RGB Imaging Should be Used to Analyze Fusarium Graminearum Growth and Estimate Deoxynivalenol Contamination

Near infrared imaging to detect Aspergillus flavus infection in three varieties of dates

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