Interpretation and explanation of computer vision classification of carambola (Averrhoa carambola L.) according to maturity stage.

The classification of carambola, also known as starfruit, according to quality parameters is usually conducted by trained human evaluators through visual inspections. This is a costly and subjective method that can generate high variability in results. As an alternative, computer vision systems (CVS) combined with deep learning (DCVS) techniques have been introduced in the industry as a powerful and an innovative tool for the rapid and non-invasive classification of fruits.

Application of a microfluidic electronic tongue based on impedance spectroscopy for coconut water analysis.

The food industry has grown with the demands for new products and their authentication, which has not been accompanied by the area of analysis and quality control, thus requiring novel process analytical technologies for food processes. An electronic tongue (e-tongue) is a multisensor system that can characterize complex liquids in a fast and simple way. Here, we tested the efficacy of an impedimetric microfluidic e-tongue setup - comprised by four interdigitated electrodes (IDE) on a printed circuit board (PCB), with four pairs of digits each, being one bare sensor and three coated with different ultrathin nanostructured films with different electrical properties - in the analysis of fresh and industrialized coconut water.

Comparison of hyperspectral imaging and spectrometers for prediction of cheeses composition.

Artisanal cheeses are part of the heritage and identity of different countries or regions. In this work, we investigated the spectral variability of a wide range of traditional Brazilian cheeses and compared the performance of different spectrometers to discriminate cheese types and predict compositional parameters. Spectra in the visible (vis) and near infrared (NIR) region were collected, using imaging (vis/NIR-HSI and NIR-HSI) and conventional (NIRS) spectrometers, and it was determined the chemical composition of seven types of cheeses produced in Brazil.

Correction: Low-cost electronic-nose (LC-e-nose) systems for the evaluation of plantation and fruit crops: recent advances and future trends.

Correction for 'Low-cost electronic-nose (LC-e-nose) systems for the evaluation of plantation and fruit crops: recent advances and future trends' by Marcus Vinicius da Silva Ferreira , , 2023, https://doi.org/10.1039/D3AY01192E.

Low-cost electronic-nose (LC-e-nose) systems for the evaluation of plantation and fruit crops: recent advances and future trends.

An electronic nose (e-nose) is a device designed to recognize and classify odors. The equipment is built around a series of sensors that detect the presence of odors, especially volatile organic compounds (VOCs), and generate an electric signal (voltage), known as e-nose data, which contains chemical information. In the food business, the use of e-noses for analyses and quality control of fruits and plantation crops has increased in recent years.

Oxidation of whey protein isolate after thermal convection and microwave heating and freeze-drying: Correlation among physicochemical and NIR spectroscopy analyses.

This study investigated the oxidative susceptibility of whey protein isolate (WPI) dispersions treated by microwave or thermal convection before freeze-drying. WPI (20 mg protein/mL) in distilled water (DW) was heated at 63 ± 2 °C for 30 min by microwave (WPI-MW) or convection heating (WPI-CH) and freeze-dried. Untreated WPI (WPI-C), WPI solubilized in DW and freeze-dried (WPI-FD), and WPI solubilized in DW, heated at 98 ± 2 °C for 2 min and freeze-dried (WPI-B) were also evaluated.

Portable near-infrared (NIR) spectrometer and chemometrics for rapid identification of butter cheese adulteration.

Artisanal cheeses are highly valued around the world for their distinct sensory characteristics, thus being prone to adulteration by substituting authentic material for cheaper products, such as vegetable oil. In this work, we developed a method based on a portable NIR spectrometer as a non-destructive and low-cost alternative to identify adulteration in butter cheese. Dataset consisted of authentic and intentionally adulterated cheeses in the laboratory and commercial cheeses, which were identified as authentic and adulterated with vegetable oil after analysis of the fatty acid profile.

Data reduction by randomization subsampling for the study of large hyperspectral datasets.

Large amount of information in hyperspectral images (HSI) generally makes their analysis (e.g., principal component analysis, PCA) time consuming and often requires a lot of random access memory (RAM) and high computing power.

Near-infrared techniques for fraud detection in dairy products: A review.

The dairy products sector is an important part of the food industry, and their consumption is expected to grow in the next 10 years. Therefore, the authentication of these products in a faster and precise way is required for the sake of public health. This review proposes the use of near-infrared techniques for the detection of food fraud in dairy products as they are faster, nondestructive, environmentally friendly, do not require sample preparation, and allow multiconstituent analysis.

Incompatibility between sodium caseinate - locust bean gum induced by NaCl and yerba mate extract.

Aqueous two-phase system (ATPS) is a technique used for the separation of biopolymers in two aqueous phases. Some combinations of biopolymers can form a water-in-water (W/W) emulsion due to steric exclusion and thermodynamic incompatibility between these biopolymers under some specific conditions. In this work, the formation of W/W emulsions composed of sodium caseinate (SCN) and locust bean gum (LBG) was evaluated, using NaCl or yerba mate extract as the driving force for the phase separation, which was described by phase's diagrams.

Near infrared hyperspectral imaging and spectral unmixing methods for evaluation of fiber distribution in enriched pasta.

Pasta is mostly composed by wheat flour and water. Nevertheless, flour can be partially replaced by fibers to provide extra nutrients in the diet. However, fiber can affect the technological quality of pasta if not properly distributed.

Occurrence of wooden breast and white striping in Brazilian slaughtering plants and use of near-infrared spectroscopy and multivariate analysis to identify affected chicken breasts.

White Striping (WS) and Wooden Breast (WB) are emerging poultry myopathies that occur worldwide, affecting the quality of meat. The aim of this study was to evaluate the occurrence of N, WS, WB, and WS/WB (myopathies combined) in chicken breast from Brazilian commercial plant, comparing (1) inspection based on visual aspect and palpation of Pectoralis major muscle, and (2) identification of these myopathies by near-infrared Spectroscopy (NIRS). Chickens slaughtered at Brazilian commercial plant at four age ranges (4 to 5, 6 to 7, 8 to 9, and 65 weeks) were inspected.

Determination of pectin content in orange peels by near infrared hyperspectral imaging.

Pectin has several purposes in the food and pharmaceutical industry making its quantification important for further extraction. Current techniques for pectin quantification require its extraction using chemicals and producing residues. Determination of pectin content in orange peels was investigated using near infrared hyperspectral imaging (NIR-HSI).

Computer Vision Classification of Barley Flour Based on Spatial Pyramid Partition Ensemble.

Imaging sensors are largely employed in the food processing industry for quality control. Flour from malting barley varieties is a valuable ingredient in the food industry, but its use is restricted due to quality aspects such as color variations and the presence of husk fragments. On the other hand, naked varieties present superior quality with better visual appearance and nutritional composition for human consumption.

Identification of fiber added to semolina by near infrared (NIR) spectral techniques.

Ingredients added in food products can increase the nutritional value, but also affect their functional properties. After processing, determination of added ingredients is difficult, thus it is important to develop rapid techniques for quantification of food ingredients. In the current work, near infrared spectroscopy (NIRS) and hyperspectral imaging (NIR-HSI) were investigated to quantify the amount of fiber added to semolina and its distribution.

Portable NIR Spectrometer for Prediction of Palm Oil Acidity.

Palm oil is widely used in the food industry, and its quality is associated with the free fatty acids (FFA) content. Determination of FFA in oil is time-consuming, requires chemicals and generates residues. There is a trend of applying process analytical technologies (PAT) for fast and nondestructive determination of oil parameters.

Classification of Chicken Parts Using a Portable Near-Infrared (NIR) Spectrophotometer and Machine Learning.

Identification of different chicken parts using portable equipment could provide useful information for the processing industry and also for authentication purposes. Traditionally, physical-chemical analysis could deal with this task, but some disadvantages arise such as time constraints and requirements of chemicals. Recently, near-infrared (NIR) spectroscopy and machine learning (ML) techniques have been widely used to obtain a rapid, noninvasive, and precise characterization of biological samples.

Classification and compositional characterization of different varieties of cocoa beans by near infrared spectroscopy and multivariate statistical analyses.

Effective and fast methods are important for distinguishing cocoa varieties in the field and in the processing industry. This work proposes the application of NIR spectroscopy as a potential analytical method to classify different varieties and predict the chemical composition of cocoa. Chemical composition and colour features were determined by traditional methods and then related with the spectral information by partial least-squares regression.

VIS-NIR spectroscopy as a process analytical technology for compositional characterization of film biopolymers and correlation with their mechanical properties.

There is an increasing interest in the use of polysaccharides and proteins for the production of biodegradable films. Visible and near-infrared (VIS-NIR) spectroscopy is a reliable analytical tool for objective analyses of biological sample attributes. The objective is to investigate the potential of VIS-NIR spectroscopy as a process analytical technology for compositional characterization of biodegradable materials and correlation to their mechanical properties.

Prediction of chicken quality attributes by near infrared spectroscopy.

In the present study, near-infrared (NIR) reflectance was tested as a potential technique to predict quality attributes of chicken breast (Pectoralis major). Spectra in the wavelengths between 400 and 2500nm were analysed using principal component analysis (PCA) and quality attributes were predicted using partial least-squares regression (PLSR). PCA performed on NIR dataset revealed the influence of muscle reflectance (L(∗)) influencing the spectra.