Feasibility of using colorimetric devices for whole and ground coffee roasting degrees prediction

BACKGROUND

Coffee roasting is one of the crucial steps in obtaining a high-quality product as it forms the product's color and flavor characteristics. Roast control is made by visual inspection or traditional instruments such as the Agtron spectrophotometer, which can have high implementation costs. Therefore, the present study evaluated colorimetric approaches (a bench colorimeter, smartphone digital images, and a colorimetric sensor) to predict the Agtron roasting degrees of whole and ground coffee. Two calibration approaches were assessed, that is, multiple linear regression and least-squares support vector machine. For that, 70 samples of whole and ground roasted coffees comprising the Agtron roasting range were prepared.

RESULTS

The results showed that all three colorimetric acquisition types were efficient for the model building, but the bench colorimeter and the smartphone digital images generally performed with good determination coefficients and low errors as measured by external validation. For the whole bean coffee, the best model presented a determination coefficient (R2 ) of 0.99 and a root-mean-squared error (RMSE) of 1.91%, while R2 of 0.99 and RMSE of 0.87% was obtained for ground coffee, both using the colorimeter.

CONCLUSION

The obtained models presented good prediction capability, as assessed by external validation and randomization tests. The obtained findings point to an alternative for coffee roasting monitoring that can lead to higher digitalization and local control of the process, even for smaller producers, due to its lower costs. © 2024 Society of Chemical Industry.

Optimizing UVC-LED application to improve the shelf life of vacuum-packed refrigerated stored Nile tilapia (Oreochromis niloticus) fillets

Although ultraviolet-C light-emitting diode (UVC-LED) has proven antimicrobial effectiveness doses needed to reach it cause adverse effects on the physicochemical quality of fish, and thus, optimization studies are crucial to boost its industrial application. This study aimed to identify optimal UVC-LED conditions for maximum shelf life extension with the least possible quality changes of refrigerated stored tilapia fillets from a central composite rotatable design (CCRD). UVC-LED powers (1, 1.38, and 1.58 mW/cm2 ) and times (500, 1800, and 2700 s) were set on the CCRD, which generated 11 treatments, including three replicate experiments. Treatments were analyzed for total aerobic psychrotrophic count, lipid oxidation, instrumental color, and texture parameters on days 0, 2, 4, 7, 11, and 14. The UVC-LED affected shelf life and physicochemical parameters in a nonlinear fashion. UVC-LED-treated fish had increased shelf life by 2.80-4.76 days and increase or decrease in lipid oxidation (0.025-0.276 mg of malondialdehyde [MDA]/kg), total color change (∆E = 3.47-9.06), and hardness (1.31-8.51 N) over the refrigerated storage depending on specific UVC-LED conditions applied. The optimal UVC-LED condition was 0.97 mW/cm2 with 2503.6 s (2428.50 mJ/cm2 ), which increased the fillet's shelf life by 2.5-fold (2 days) while maintaining quality closer to the original throughout refrigerated storage, resulting in ∆E < 5, an increase of only 0.05 mg of MDA/kg, and preservation of the decrease in hardness by 3.38 N compared to its control counterparts. Therefore, it represents an eco-friendly technology that can easily scaled industrially to enhance the sustainable fish production chain. PRACTICAL APPLICATION: The high fish perishability is a global concern due to food safety risks and waste generation impacting the environment adversely, especially nowadays, where fish production and consumption have increased, and there are more evident efforts to sustainable production. UVC-LED is an eco-friendly technology with proven antimicrobial effectiveness but doses needed to reach this effect enhance oxidative degradation. Despite that, optimization studies concerning the maximum shelf life extension while retaining the physicochemical quality of refrigerated stored fish are a gap in the literature and a barrier to its industrial application. Our findings are helpful in sustainably enhancing the fish production chain.

Exploring Strategies to Mitigate the Lightness Effect on the Prediction of Soybean Oil Content in Blends of Olive and Avocado Oil Using Smartphone Digital Image Colorimetry

Extra virgin olive oil (EVOO) and avocado oil (AVO) are recognized for their unique sensory characteristics and bioactive compounds. Declared blends with other vegetable oils are legal, but undeclared mixing is a common type of fraud that can affect product quality and commercialization. In this sense, this study explored strategies to mitigate the influence of lighting in order to make digital image colorimetry (DIC) using a smartphone more robust and reliable for predicting the soybean oil content in EVOO and AVO blends. Calibration models were obtained by multiple linear regression using the images' RGB values. Corrections based on illuminance and white reference were evaluated to mitigate the lightness effect and improve the method's robustness and generalization capability. Lastly, the prediction of the built model from data obtained using a distinct smartphone was assessed. The results showed models with good predictive capacities, R2 > 0.9. Generally, models solely based on GB values showed better predictive performances. The illuminance corrections and blank subtraction improved the predictions of EVOO and AVO samples, respectively, for image acquisition from distinct smartphones and lighting conditions as evaluated by external validation. It was concluded that adequate data preprocessing enables DIC using a smartphone to be a reliable method for analyzing oil blends, minimizing the effects of variability in lighting and imaging conditions and making it a potential technique for oil quality assurance.

Combined UV-C Technologies to Improve Safety and Quality of Fish and Meat Products: A Systematic Review

This study aimed to identify the best UV-C combined treatments for ensuring the safety and quality of fish and meat products. A total of 4592 articles were screened in the relevant databases, and 16 were eligible studies. For fish, the most effective treatments to reduce Gram-negative and Gram-positive bacteria were UV-C at 0.5 J/cm² + non-thermal atmospheric plasma (NTAP) for 8 min (33.83%) and 1% Verdad N6 + 0.05 J/cm² + vacuum packaging (25.81%), respectively. An oxygen absorber with 0.102 J/cm² was the best combined treatment, reducing lipid oxidation (65.59%), protein oxidation (48.95), color (ΔE = 4.51), and hardness changes (18.61%), in addition to a shelf-life extension of at least 2 days. For meat products, Gram-negative bacteria were more reduced by nir-infrared heating (NIR-H; 200.36 µW/cm²/nm) combined with 0.13 J/cm² (70.82%) and 0.11 J/cm² (52.09%). While Gram-positive bacteria by 0.13 J/cm² with NIR-H (200.36 µW/cm²/nm), 1, 2, or 4 J/cm² with flash pasteurization (FP) during 1.5 or 3 s, and 2 J/cm² with FP for 0.75 s (58.89-67.77%). LAE (5%) + 0.5 J/cm² was promising for maintaining color and texture. UV-C combined technologies seem to be a cost-effective alternative to ensure safety with little to no quality changes in fish and meat products.

ATR-FTIR spectroscopy and chemometrics as a quick and simple alternative for discrimination of SARS-CoV-2 infected food of animal origin

Alternative routes such as virus transmission or cross-contamination by food have been suggested, due to reported cases of SARS-CoV-2 in frozen chicken wings and fish or seafood. Delay in routine testing due to the dependence on the PCR technique as the standard method leads to greater virus dissemination. Therefore, alternative detection methods such as FTIR spectroscopy emerge as an option. Here, we demonstrate a fast (3 min), simple and reagent-free methodology using attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy for discrimination of food (chicken, beef and fish) contaminated with the SARS-CoV-2 virus. From the IR spectra of the samples, the "bio-fingerprint" (800 - 1900 cm^-1) was selected to investigate the distinctions caused by the virus contamination. Exploratory analysis of the spectra, using Principal Component of Analysis (PCA), indicated the differentiation in the data due to the presence of single bands, marked as contamination from nucleic acids including viral RNA. Furthermore, the partial least squares discriminant analysis (PLS-DA) classification model allowed for discrimination of each matrix in its pure form and its contaminated counterpart with sensitivity, specificity and accuracy of 100 %. Therefore, this study indicates that the use of ATR-FTIR can offer a fast and low cost and not require chemical reagents and with minimal sample preparation to detect the SARS-CoV-2 virus in food matrices, ensuring food safety and non-dissemination by consumers.

Combination of RT-LAMP and fluorescence spectroscopy using chemometric techniques for an ultra-sensitive and rapid alternative for the detection of SARS-CoV-2

The increased spread of COVID-19 caused by SARS-CoV-2 has made it necessary to develop more efficient, fast, accurate, specific, sensitive and easy-to-use detection platforms to overcome the disadvantages of gold standard methods (RT-qPCR). Here an approach was developed for the detection of the SARS-CoV-2 virus using the loop-mediated isothermal amplification (LAMP) technique for SARS-CoV-2 RNA target amplification in samples of nasopharyngeal swabs. The discrimination between positive and negative SARS-CoV-2 samples was achieved by using fluorescence spectra generated by the excitation of the LAMP's DNA intercalator dye at λ497 nm in a fluorescence spectrophotometer and chemometric tools. Exploratory analysis of the 83 sample spectra using principal component analysis (PCA) indicated a trend in differentiation between positive and negative samples resulting from the peak emission of the fluorescent dye. The classification was performed by partial least squares discriminant analysis (PLS-DA) achieving a sensitivity, a specificity and an accuracy of 100%, 95% and 89%, respectively for the discrimination between negative and positive samples from 1.58 to 0.25 ng L^-1 after LAMP amplification. Therefore, this study indicates that the use of the LAMP technique in fluorescence spectroscopy may offer a fast (<1 hour), sensitive and low-cost method.

Inactivation of Multi-Drug Resistant Non-Typhoidal Salmonella and Wild-Type Escherichia coli STEC Using Organic Acids: A Potential Alternative to the Food Industry

Salmonella and Escherichia coli are the main bacterial species involved in food outbreaks worldwide. Recent reports showed that chemical sanitizers commonly used to control these pathogens could induce antibiotic resistance. Therefore, this study aimed to describe the efficiency of chemical sanitizers and organic acids when inactivating wild and clinical strains of Salmonella and E. coli, targeting a 4-log reduction. To achieve this goal, three methods were applied. (i) Disk-diffusion challenge for organic acids. (ii) Determination of MIC for two acids (acetic and lactic), as well as two sanitizers (quaternary compound and sodium hypochlorite). (iii) The development of inactivation models from the previously defined concentrations. In disk-diffusion, the results indicated that wild strains have higher resistance potential when compared to clinical strains. Regarding the models, quaternary ammonium and lactic acid showed a linear pattern of inactivation, while sodium hypochlorite had a linear pattern with tail dispersion, and acetic acid has Weibull dispersion to E. coli. The concentration to 4-log reduction differed from Salmonella and E. coli in acetic acid and sodium hypochlorite. The use of organic acids is an alternative method for antimicrobial control. Our study indicates the levels of organic acids and sanitizers to be used in the inactivation of emerging foodborne pathogens.

Everybody loves cheese: crosslink between persistence and virulence of Shiga-toxin Escherichia coli

General cheese manufacturing involves high temperatures, fermentation and ripening steps that function as hurdles to microbial growth. On the other hand, the application of several different formulations and manufacturing techniques may create a bacterial protective environment. In cheese, the persistent behavior of Shiga toxin-producing Escherichia coli (STEC) relies on complex mechanisms that enable bacteria to respond to stressful conditions found in cheese matrix. In this review, we discuss how STEC manages to survive to high and low temperatures, hyperosmotic conditions, exposure to weak organic acids, and pH decreasing related to cheese manufacturing, the cheese matrix itself and storage. Moreover, we discuss how these stress responses interact with each other by enhancing adaptation and consequently, the persistence of STEC in cheese. Further, we show how virulence genes eae and tir are affected by stress response mechanisms, increasing either cell adherence or virulence factors production, which leads to a selection of more resistant and virulent pathogens in the cheese industry, leading to a public health issue.

Combination of peracetic acid and ultrasound reduces Salmonella Typhimurium on fresh lettuce (Lactuca sativa L. var. crispa)

Salmonella outbreaks related to fruits and vegetables have been reported being lettuce one of the most contaminated. Peracetic acid (PA) at 50 mg/L, sodium dichloroisocyanurate (SD) at 100 mg/L, and the combination of SD at 100 mg/L and babaçu coconut (Attalea speciosa) oil detergent at 100 mg/L were applied to fresh lettuce. Natural contaminant microbiota, physicochemical characteristics, and sensory attributes were evaluated. PA and SD reduced mesophilic aerobic counts by 2.1 and 1.5 log cfu/g, respectively. The most efficient treatment in reducing natural microbiota (i.e., PA) was applied alone and in combination with ultrasound (US). It reduced Salmonella enterica Typhimurium counts to undetectable levels (< 1 log cfu/g). US further reduced S. Typhimurium counts by 0.6 log cfu/g in relation to PA, treatment which lessened the pH but increased the titratable acidity of lettuce, but did not cause total color difference. Therefore, the combination of PA and US holds a potential industrial application for sanitization purposes.