Electronic eye for the prediction of parameters related to grape ripening

Orlandi, Giorgia; Calvini, Rosalba; Pigani, Laura; Foca, Giorgia; Simone, Giuseppe Vasile; Antonelli, Andrea; Ulrici, Alessandro

doi:10.1016/j.talanta.2018.04.076

Cited by 22 publications

(24 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Antonelli et al 9 developed a feature selection/classification method that employs a one‐dimensional signal called “colourgram,” which is a contiguous sequence of the histograms of the three R, G and B channels, including in the dataset several additional color‐related variables derived from RGB image. For the construction of “colourgrams,” each RGB image is initially unfolded into a two‐dimensional matrix, where the rows contain the number of segmented pixels and the three columns comprising to the R, G, and B channels.…”

Section: Digital Image‐based Chemical Analysismentioning

confidence: 99%

“…In Section 2, a comprehensive discussion of the different modalities of DIB‐analytical approaches derived from color histograms as well as their acronyms will be presented. As a consequence, for the purposes of conceptual uniformity, computer vision‐based analytical chemistry (CVAC) 3,4 and “Colourgrams” 9 will be differentiated from a modality that has been not yet categorized in the literature, needing to be placed with a most suitable expression, here proposed as Chemometrics‐Assisted Color Histogram‐based Analytical System and its acronym CACHAS. Then, the first aim is to clearly inform readers about the terminology, general characteristics, fundamentals, and instrumentation (i.e., manifold components) of CACHAS, considering the practical perspectives on how to direct further development of analytical methods by both newcomers and experts in the field, as detailed in Sections 4 and 5, respectively.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Chemometrics‐assisted color histogram‐based analytical systems

Diniz

2020

Journal of Chemometrics

View full text Add to dashboard Cite

This review systematizes for the first time the here called "Chemometricsassisted color histogram-based analytical systems" under the acronym CACHAS. A comprehensive discussion of the fundamentals, general characteristics, and applications are presented in order to direct practical aspects for developing methods that use color histograms as input data for the construction of chemometric models. For this, analytical information is rapidly acquired using a simple image acquisition device (such as digital camera, webcam, scanner, or smartphone), without need for any image processing, other than extraction of the histograms, which are constructed by counting the frequency distribution of the different color tones (conveniently specified through a color space) of all pixels delimited by a region of interest in a digital image. As a consequence, CACHAS have been increasingly used for qualitative and quantitative purposes in food, agricultural, forensic, biomedical, and microbiological analysis, reinforcing the principles of green analytical chemistry.

show abstract

Section: Digital Image‐based Chemical Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Chemometrics‐assisted color histogram‐based analytical systems

Diniz

2020

Journal of Chemometrics

View full text Add to dashboard Cite

show abstract

“…Using the color data set, a calibration model is employed to relate the images' color to the grapes' phenolic composition using an analytical reference method. Therefore the ripening trend can be followed (88). Yang et al (89) performed the characterization of physical properties and electronic sensory analysis of citrus oil-based nanoemulsions.…”

Section: Electronic Eye In the Food Industrymentioning

confidence: 99%

Electronic Nose, Tongue and Eye: Their Usefulness for the Food Industry

Ordoñez-Araque

Rodríguez-Villacres

Urresto-Villegas

2020

Vitae

View full text Add to dashboard Cite

Background: The electronic nose, tongue, and eye are futuristic technologies that have been used for many years; they have been gaining market in different types of industries and can increasingly be found in the food area; their function is to determine sensory characteristics (smell, aroma, and flavor) and objective visuals, without the subjectivity that can be represented by sensory analysis by people (the study that can complement the analysis of machines, without being exclusive). Objectives: Find the main generalities of these mechanisms, their sensors, software, mechanism of action, and applications within the food industry. Methods: A search was carried out in the main databases of indexed articles, with terms that allowed collecting the necessary information, and 89 articles were used that met different inclusion criteria. Results: The main outcomes were to understand the operation of each of these technologies, what their main components are, and how they can be linked in the beer, wine, oil, fruit, vegetable, dairy, etc. industry to determine their quality, safety, and fraud. Conclusions: The use of electronic nose, tongue, and eye is found in more food industries every day. Its technology continues to evolve; the future of sensory analysis will undoubtedly apply these mechanisms due to the reliability, speed, and reproducibility of the results.

show abstract

“…This new perspective on analytical instrumentation has been focused on using bio-inspired systems that base their operation on the emulation of human senses to determine food characteristics, such as color, shape or size. In particular, the Electronic Eye (EE) has been designed to mimic human vision and analyze the color and some other attributes related to the sample's appearance [7,8], and it is usually based on computer vision, colorimetric or spectrophotometry methods [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Electronic Eye for Identification of Tequila Samples

Gómez

Bueno

Gutiérrez

2020

The 1st International Electronic Conference on Biosensors

View full text Add to dashboard Cite

The present work reports the potential of a bio-inspired system based on spectrometry, also known as Electronic Eye (EE), capable of detecting different Tequila samples. The reported system analyzes small volumes of Tequila Reposado and Blanco by calculating samples’ absorbances, using a low cost and portable instrumentation employing a CCD camera. The absorbance imaging method consisted of exciting samples with light passes through an 8MP camera connected to a Raspberry Pi Card. The camera’s image data are analyzed using MATLAB 2018b to be represented in Red, Green and Blue (RGB) components for each pixel, in order to get an approximation of the absorbance and the Surface Color Index (Isc) associated with sample concentration. Using the developed EE, it was possible to identify seven different kinds and brands of Tequila. From the obtained results, it was observed that the average absorbance of the Tequila Reposado was greater than the absorbance of the Tequila Blanco. Otherwise, with the Isc, the Tequila Blanco color index is lower concerning the Tequila Reposado’s. Finally, the EE allowed the identification of Tequila samples with reproducibility and repeatability.

show abstract

Electronic eye for the prediction of parameters related to grape ripening

Cited by 22 publications

References 32 publications

Chemometrics‐assisted color histogram‐based analytical systems

Chemometrics‐assisted color histogram‐based analytical systems

Electronic Nose, Tongue and Eye: Their Usefulness for the Food Industry

Electronic Eye for Identification of Tequila Samples

Contact Info

Product

Resources

About