Data of: Integration of handheld NIR and machine learning for the development of a “Measure & Monitor” technology for chicken meat authenticity

Near Infrared spectroscopy data of chicken meat (fillets) from multiple growth conditions and countries of origin (Netherlands and Ireland)

Big (Bio)Chemical Data Mining Using Chemometric Methods: A Need for Chemists

This review aims to demonstrate abilities to analyze Big (Bio)Chemical Data (BBCD) with multivariate chemometric methods and to show some of the more important challenges of modern analytical researches. In this review, the capabilities and versatility of chemometric methods will be discussed in light of the BBCD challenges that are being encountered in chromatographic, spectroscopic and hyperspectral imaging measurements, with an emphasis on their application to omics sciences. In addition, insights and perspectives on how to address the analysis of BBCD are provided along with a discussion of the procedures necessary to obtain more reliable qualitative and quantitative results. In this review, the importance of Big Data and of their relevance to (bio)chemistry are first discussed. Then, analytical tools which can produce BBCD are presented as well as some basics needed to understand prospects and limitations of chemometric techniques when they are applied to BBCD are given. Finally, the significance of the combination of chemometric approaches with BBCD analysis in different chemical disciplines is highlighted with some examples. In this paper, we have tried to cover some of the applications of big data analysis in the (bio)chemistry field. However, this coverage is not extensive covering everything done in the field.Hadi Parastar would like to thank Sharif University of Technology (SUT) of Iran for financial support for a short sabbatical leave at IDAEA-CSIC of Barcelona. Roma Tauler would like to thank the European Research Council for the European Union’s Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement no. 320737.Peer reviewe

Data of: Integration of handheld NIR and machine learning for the development of a “Measure & Monitor” technology for chicken meat authenticity

Near Infrared spectroscopy data of chicken meat (fillets) from multiple growth conditions and countries of origin (Netherlands and Ireland)

Data of: Integration of handheld NIR and machine learning for the development of a “Measure & Monitor” technology for chicken meat authenticity

Near Infrared spectroscopy data of chicken meat (fillets) from multiple growth conditions and countries of origin (Netherlands and Ireland). The data was recorded by applying a MicroNIR Pro (Viavi) device equipped with the standard issue collar by applying on the samples in three different ways: (i) directly on the meat, (ii) through the top foil of the package (i.e. with an air pocket between the foil and the breast fillet) and (iii) through the top foil packaging bottom up (i.e. no air pocket between the foil and the breast fillet). Five replicates were recorded per sample

Data of: Integration of handheld NIR and machine learning for the development of a “Measure & Monitor” technology for chicken meat authenticity

Near Infrared spectroscopy data of chicken meat (fillets) from multiple growth conditions and countries of origin (Netherlands and Ireland). The data was recorded by applying a MicroNIR Pro (Viavi) device equipped with the standard issue collar by applying on the samples in three different ways: (i) directly on the meat, (ii) through the top foil of the package (i.e. with an air pocket between the foil and the breast fillet) and (iii) through the top foil packaging bottom up (i.e. no air pocket between the foil and the breast fillet). Five replicates were recorded per sample

Electrochemical Degradation of Reactive Black 5 Using Three-Dimensional Electrochemical System Based on Multiwalled Carbon Nanotubes

The removal of Reactive Black 5 (RB5) dye and chemical oxygen demand (COD) was investigated using a three-dimensional (3D) electrochemical (3DE) reactor with multiwalled carbon nanotubes (MWCNTs). The experiments were performed according to a Taguchi design model, with the variables being the solution pH (2-9), current density (10-25 mA/cm2), reaction time (15-60 min), MWCNT concentration (25-200 mg/L), and RB5 concentration (25-100 mg/L). The best conditions for optimum removal of RB5 and COD were pH 3, MWCNT concentration 200 mg/L, current density 15 mA/cm2, RB5 concentration 100 mg/L, and reaction time 60 min. Among the main factors, the solution pH for removal of COD and RB5 and the current density for energy consumption had the highest impact. The 3D system generated more H2O2 and OH radicals compared with a two-dimensional (2D) system because the MWCNTs act as microelectrodes in the optimal conditions. In the 3D process, the production of high levels of reactive species led to an increase in the degradation of RB5 into aromatic compounds and various acids. © 2019 American Society of Civil Engineers