A modified mid-level data fusion approach on electronic nose and FT-NIR data for evaluating the effect of different storage conditions on rice germ shelf life

Malegori, Cristina; Buratti, Susanna; Benedetti, Simona; Oliveri, Paolo; Ratti, S.; Cappa, C.; Lucisano, M.

doi:10.1016/j.talanta.2019.120208

Cited by 43 publications

(16 citation statements)

References 30 publications

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“…Using the olfactory machine, the durability of various products such as tomatoes (Gómez et al, 2008), apples (Brezmes et al, 2001;Saevels et al, 2004), raw milk and meat (Amari et al, 2009), Valerianella (Cortellino et al, 2018), fried potatoes (Chatterjee et al, 2014), rice (Malegori et al, 2020), essential oils from herbs and fruits (Rasekh et al, 2021), and agricultural products (Baietto & Wilson, 2015;Gancarz et al, 2021;Marek et al, 2020;Wilson, 2013) has been determined.…”

mentioning

confidence: 99%

Identification of olfactory characteristics of edible oil during storage period using metal oxide semiconductor sensor signals and ANN methods

Karami

Rasekh

Mirzaee‐Ghaleh

2021

J. Food Process. Preserv.

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In recent decades, industrialization and modernization of the communities have decreased the daily activities of the people; thus, physicians are increasingly recommended the use of low-cholesterol vegetable oil. The nutritional value of the vegetable oils is incomparable with the animal-based or hydrogenated vegetable oils. Liquid vegetable oils obtained from sesame, olive, corn, soybean, and sunflower are among the best edible oils for human health. These oils contain considerable amounts of unsaturated fatty acids, which are vital for human health as they reduce the chance of hyperglycemia, atherosclerosis, and other cardiovascular diseases. Therefore, a vegetable oil obtained from the oilseeds is the best edible oil.Vegetable oils are the main source of unsaturated fatty acids and other substances, for example, phytosterols and tocopherols in the human diet. Oxidation is an important chemical reaction that can affect the nutritional value and sensory quality of vegetable oils.Fatty acids are the main compounds of oil that undergo oxidation

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mentioning

confidence: 99%

Identification of olfactory characteristics of edible oil during storage period using metal oxide semiconductor sensor signals and ANN methods

Karami

Rasekh

Mirzaee‐Ghaleh

2021

J. Food Process. Preserv.

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“…This can be potentially overcome by combining NIR spectroscopy with other analytical methods. Studies developed by [97] allowed to develop a tandem approach of monitoring rice germ shelf life during storage using NIR and a portable e-nose. Le et al proposed a study that combines deep learning with NIR to provide a much faster method of cereal analysis compratively to traditional NIR models [98].…”

Section: Practical Applications Of Nir Spectroscopy and Chemometrics 21 Nir Spectroscopy In Rice Analysis: Identification And Classificatmentioning

confidence: 99%

Near-Infrared Spectroscopy and Machine Learning: Analysis and Classification Methods of Rice

Sampaio¹,

Brites²

2022

Integrative Advances in Rice Research

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Nowadays, the conventional biochemical methods used to differentiate and characterize rice types, biochemical properties, authentication, and contamination issues are difficult to implement due to the high cost of reagents, time requirement and environmental issues. Actually, the success of agri-food technology is directly related to the quality of analysis of experimental data acquired by sensors or techniques such as the infrared-spectroscopy. To overcome these technical limitations, a rapid and non-destructive methodology for discrimination and classification of rice has been investigated. Near-infrared spectroscopy is considered as fast, clean, and non-destructive analytical tools and its spectra present significant biomolecular information that must be analysed by sophisticated methodologies. Machine learning plays an important role in the analysis of the spectral data being used several methods such as Partial Least Squares, Principal Component Analysis, Partial Least Squares-Discriminant Analysis, Support Vector Machine, Artificial Neuronal Network, among others which can successfully be applied for food classification and discrimination as well as in terms of authentication and contamination issues. The quality control of rice is extremely important at every stage of production, beginning with estimation of raw agricultural materials and monitoring their quality during storage, estimating food quality during the production process and of the final products as well as the determination of their authenticity and the detection of adulterants.

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“…Nevertheless, in this study, the authors stated that their findings were incomplete, and they need to consider a larger number of samples for a further exhaustive investigation. In [34], this work was intended to explore the possibility of increasing the shelf life of rice germ by decreasing water activity and considering the storage atmosphere packaging. A portable e-nose and a Fourier-transform NIR (FT-NIR) spectrometer were used to assess the quality of this by-product during the storage.…”

Section: B System Developmentmentioning

confidence: 99%

A Review on Electronic Nose: Coherent Taxonomy, Classification, Motivations, Challenges, Recommendations and Datasets

et al. 2021

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Context: Quality Control (QC) has been constantly an essential concern in many fields like food industry production, medical drugs, environmental protection, and so on. An odor or flavor, as a global fingerprint, can be implemented as a non-invasive mechanism for quality assurance. This computer-based approach can assure accurate detection and precise identification of the product quality or manufactured goods.Objective: This paper aims to achieve a systematic review about e-nose by introducing the achievements made by researchers in this area, to summarize their findings, to provide motivations and challenges to new researchers in the field of e-nose. Methods:The articles that were being utilized in the e-nose field were systematically achieved using three search engines: The online library of IEEE Explore, Web of Science and Science Direct for time span of 7 years (from 2013 to 2020). Both medical literature reviews and technical reviews were considered in the criteria of the research for wider understanding in the field of e-nose. The articles were categorized according to the objective of the research and projected into four classes. Upon completion of screening process 333 research papers using the exclusion and inclusion conditions, as the final set 54 articles were selected. Results:The taxonomy of this research was classified into four categories. The first one included the suggested methods that introduced the utilization of the e-nose for classification purposes (9/54 papers). The second category comprises the methods related to the development of e-nose (24/54 papers). The third one included the review studies about the e-nose (8/54 papers). The fourth group comprises comparative studies and evaluation (13/54 papers).Discussion: This systematic review contributes for a clearer understanding and a full insight in the e-nose research field by surveying and categorizing pertinent research efforts.

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A modified mid-level data fusion approach on electronic nose and FT-NIR data for evaluating the effect of different storage conditions on rice germ shelf life

Cited by 43 publications

References 30 publications

Identification of olfactory characteristics of edible oil during storage period using metal oxide semiconductor sensor signals and ANN methods

Identification of olfactory characteristics of edible oil during storage period using metal oxide semiconductor sensor signals and ANN methods

Near-Infrared Spectroscopy and Machine Learning: Analysis and Classification Methods of Rice

A Review on Electronic Nose: Coherent Taxonomy, Classification, Motivations, Challenges, Recommendations and Datasets

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