Probabilistic topic modelling in food spoilage analysis: A case study with Atlantic salmon (Salmo salar)

La-Ce-MOF nanocomposite coated quartz crystal microbalance gas sensor for the detection of amine gases and formaldehyde

Trimethylamine (TMA), Dimethylamine (DMA), Ammonia (NH3) and formaldehyde (HCHO) are typical volatile gases and able to cause great damage to the environment and the human body, and they may appear along in some particular cases such as marine meat spoilage. However, gas sensors can detect all the 4 hazardous gases simultaneously have rarely been reported. In this study, a quartz crystal microbalance (QCM) gas sensor modified with La-Ce-MOF was employed for the detection of 4 target gases (TMA, DMA, NH3 and HCHO). The sensor exhibited excellent stability (63 days), selectivity (3.51 Hz/(μmoL/L) for TMA, 4.19 Hz/(μmoL/L) for DMA, 3.14·Hz/(μmoL/L) for NH3 and 3.08·Hz/(μmoL/L) for HCHO), robustness and sensitivity towards target gases detection. Vienna Ab-initio Simulation Package calculations showed that this superior sensing performance was attributed to the preferential adsorption of target gas molecules onto the nanomicrospheres via hydrogen bond. The adsorption energy was - 0.4329 eV for TMA, - 0.5204 eV for DMA, - 0.6823 eV for NH3 and - 0.7576 eV for HCHO, all of which are physically adsorbed. In the detection of hazardous gases, sensor surface active sites were often susceptible to environmental factors and interfering substances, leading to a decrease in the sensitivity of the gas sensor, which in turn affects the signal accuracy in practical applications. This issue has been effectively addressed and the sensor has been implemented for the assessment of the salmon meat freshness, which may contribute to further advancements in the development of QCM gas sensors for monitoring food quality, human beings health and environment safety.

Rapid and non-destructive microbial quality prediction of fresh pork stored under modified atmospheres by using selected-ion flow-tube mass spectrometry and machine learning

Volatile organic compounds (VOCs) indicative of pork microbial spoilage can be quantified rapidly at trace levels using selected-ion flow-tube mass spectrometry (SIFT-MS). Packaging atmosphere is one of the factors influencing VOC production patterns during storage. On this basis, machine learning would help to process complex volatolomic data and predict pork microbial quality efficiently. This study focused on (1) investigating model generalizability based on different nested cross-validation settings, and (2) comparing the predictive power and feature importance of nine algorithms, including Artificial Neural Network (ANN), k-Nearest Neighbors, Support Vector Regression, Decision Tree, Partial Least Squares Regression, and four ensemble learning models. The datasets used contain 37 VOCs' concentrations (input) and total plate counts (TPC, output) of 350 pork samples with different storage times, including 225 pork loin samples stored under three high-O2 and three low-O2 conditions, and 125 commercially packaged products. An appropriate choice of cross-validation strategies resulted in trustworthy and relevant predictions. When trained on all possible selections of two high-O2 and two low-O2 conditions, ANNs produced satisfactory TPC predictions of unseen test scenarios (one high-O2 condition, one low-O2 condition, and the commercial products). ANN-based bagging outperformed other employed models, when TPC exceeded ca. 6 log CFU/g. VOCs including benzaldehyde, 3-methyl-1-butanol, ethanol and methyl mercaptan were identified with high feature importance. This elaborated case study illustrates great prospects of real-time detection techniques and machine learning in meat quality prediction. Further investigations on handling low VOC levels would enhance the model performance and decision making in commercial meat quality control.

Selected-ion flow-tube mass spectrometry for the identification of volatile spoilage markers for fresh pork packaged under modified atmospheres

Microbial behavior during meat storage leads to the generation of volatile organic compounds (VOCs) and unpleasant off-odors. This study focused on a novel real-time analytical method, selected-ion flow-tube mass spectrometry (SIFT-MS), to monitor VOC quality and identify spoilage indicators for fresh pork stored under different packaging atmospheres (air, 70/0/30, 70/30/0, 5/30/65, 0/30/70 - v/v% O₂/CO₂/N₂) at 4 °C. A comprehensive selection methodology was used to identify compounds with good instrumental data quality as well as a strong relationship with microbial growth and olfactory rejection. Based on the volatolome quantified by SIFT-MS, storage periods and conditions can be discriminated using multivariate statistics. Acetoin (or ethyl acetate) represented a significant pork quality marker for high-O₂ conditions, whereas ethanol, 3-methylbutanal and sulfur compounds can indicate the anaerobic storage progress. Considering the applicability in monitoring different VOC profiles, SIFT-MS is expected to be promising in many storage scenarios to improve analytical efficiency and ensure reliability.

Use of industry 4.0 technologies to reduce and valorize seafood waste and by-products: A narrative review on current knowledge

Fish and other seafood products represent a valuable source of many nutrients and micronutrients for the human diet and contribute significantly to global food security. However, considerable amounts of seafood waste and by-products are generated along the seafood value and supply chain, from the sea to the consumer table, causing severe environmental damage and significant economic loss. Therefore, innovative solutions and alternative approaches are urgently needed to ensure a better management of seafood discards and mitigate their economic and environmental burdens. The use of emerging technologies, including the fourth industrial revolution (Industry 4.0) innovations (such as Artificial Intelligence, Big Data, smart sensors, and the Internet of Things, and other advanced technologies) to reduce and valorize seafood waste and by-products could be a promising strategy to enhance blue economy and food sustainability around the globe. This narrative review focuses on the issues and risks associated with the underutilization of waste and by-products resulting from fisheries and other seafood industries. Particularly, recent technological advances and digital tools being harnessed for the prevention and valorization of these natural invaluable resources are highlighted.

Investigating the effects of the outbreak of COVID-19 on perishable food supply chains: an empirical study using PLS-SEM

Purpose

At the end of 2019, the first case of the Corona Virus Disease (COVID-19) was reported in Wuhan city of China. The disease was declared a pandemic without imagining the magnitude of damage currently caused in all branches of the economy. One of the most affected sectors was food and mostly perishable food (PF), which are more susceptible to environmental conditions. Thus, the research examines the effect of the COVID-19 outbreak on Ecuador's perishable food supply chains (PFSCs) during the pandemic. It contributes to new results on the special issue (SI) PFSC response to event risk and uncertainty, such as those that generated the pandemic.

Design/methodology/approach

The data used are from primary information sources, which were collected through a questionnaire. The questionnaire was applied to 298 companies belonging to the sector, and later the information was processed through partial least squares structural equation model. The convergent validity, discriminate and robustness tests provide arguments for the suitability of the model. Therefore, the findings are reliable and valid for the adequate measures to improve the PFSC due to a COVID-19 outbreak.

Findings

The results show that the perception of personal risk (PPR) produced by COVID-19 has caused the companies of the PFSC to adopt preventive policies (PO) to avoid contagion and guarantee the operation of the companies. In addition, the PPR has been responsible for the alterations in the demand and price (DP) of PF. Next, PO and DP have a significant effect on PFSC, which shows the evidence favouring the malfunction of PFSC operations due to anti-contagion PO, the mismatch of DP. On the contrary, circular economy practices contribute to the excellent performance of the PFSC. Finally, the research suggests some policy implications to consider in improving the PFSC.

Originality/value

This study is the first to be carried out in Ecuador's country on the PFSC; its contribution is unprecedented and makes it a road-map to be considered to guarantee the correct functioning of the PFSCs, and it will provide policymakers with valid elements to design efficient PFSCs that better respond to unforeseen events and uncertainties. Future research will focus on analysing the management of PF consumption in Ecuador during the pandemic.