Recent developments in applications of MRI techniques for foods and agricultural produce—an overview

Design, Fabrication, and Applications of SERS Substrates for Food Safety Detection: Review

Sustainable and safe food is an important issue worldwide, and it depends on cost-effective analysis tools with good sensitivity and reality. However, traditional standard chemical methods of food safety detection, such as high-performance liquid chromatography (HPLC), gas chromatography (GC), and tandem mass spectrometry (MS), have the disadvantages of high cost and long testing time. Those disadvantages have prevented people from obtaining sufficient risk information to confirm the safety of their products. In addition, food safety testing, such as the bioassay method, often results in false positives or false negatives due to little rigor preprocessing of samples. So far, food safety analysis currently relies on the enzyme-linked immunosorbent assay (ELISA), polymerase chain reaction (PCR), HPLC, GC, UV-visible spectrophotometry, and MS, all of which require significant time to train qualified food safety testing laboratory operators. These factors have hindered the development of rapid food safety monitoring systems, especially in remote areas or areas with a relative lack of testing resources. Surface-enhanced Raman spectroscopy (SERS) has emerged as one of the tools of choice for food safety testing that can overcome these dilemmas over the past decades. SERS offers advantages over chromatographic mass spectrometry analysis due to its portability, non-destructive nature, and lower cost implications. However, as it currently stands, Raman spectroscopy is a supplemental tool in chemical analysis, reinforcing and enhancing the completeness and coverage of the food safety analysis system. SERS combines portability with non-destructive and cheaper detection costs to gain an advantage over chromatographic mass spectrometry analysis. SERS has encountered many challenges in moving toward regulatory applications in food safety, such as quantitative accuracy, poor reproducibility, and instability of large molecule detection. As a result, the reality of SERS, as a screening tool for regulatory announcements worldwide, is still uncommon. In this review article, we have compiled the current designs and fabrications of SERS substrates for food safety detection to unify all the requirements and the opportunities to overcome these challenges. This review is expected to improve the interest in the sensing field of SERS and facilitate the SERS applications in food safety detection in the future.

Early detection of cotton verticillium wilt based on root magnetic resonance images

Verticillium wilt (VW) is often referred to as the cancer of cotton and it has a detrimental effect on cotton yield and quality. Since the root system is the first to be infested, it is feasible to detect VW by root analysis in the early stages of the disease. In recent years, with the update of computing equipment and the emergence of large-scale high-quality data sets, deep learning has achieved remarkable results in computer vision tasks. However, in some specific areas, such as cotton root MRI image task processing, it will bring some challenges. For example, the data imbalance problem (there is a serious imbalance between the cotton root and the background in the segmentation task) makes it difficult for existing algorithms to segment the target. In this paper, we proposed two new methods to solve these problems. The effectiveness of the algorithms was verified by experimental results. The results showed that the new segmentation model improved the Dice and mIoU by 46% and 44% compared with the original model. And this model could segment MRI images of rapeseed root cross-sections well with good robustness and scalability. The new classification model improved the accuracy by 34.9% over the original model. The recall score and F1 score increased by 59% and 42%, respectively. The results of this paper indicate that MRI and deep learning have the potential for non-destructive early detection of VW diseases in cotton.

Effects of ε-polylysine and chitooligosaccharide Maillard reaction products on quality of refrigerated sea bass fillets

BACKGROUND

The Maillard reaction is a promising and safe method for obtaining chitooligosaccharide conjugates with proteins or peptides as food preservatives. This study aims to investigate the moisture state, physicochemical properties, and shelf-life of sea bass fillets treated with ε-polylysine (ε-PL) and chitooligosaccharides (COS), which are Maillard reaction products (LC-MRPs), during refrigerated storage.

RESULTS

The results of microbiological analysis and confocal laser scanning microscope (CLSM) revealed that LC-MRPs could retard microbial growth effectively. Compared with control, other treated groups could strongly retard the increase in the thiobarbituric acid (TBA) value, the K-value and the total volatile basic nitrogen (TVB-N) value, and also inhibited the softening of texture and the accumulation of biogenic amines in fish. The results of low-field nuclear magnetic resonance (LF-NMR) and magnetic resonance imaging (MRI) indicate that LC-MRPs could delay the water migration of fillets and increase water holding capacity (WHC). Through sensory evaluation, the application of LC-MRPs increased the shelf-life of refrigerated sea bass fillets for another 9 days.

CONCLUSION

Maillard reaction products derived from chitooligosaccharides and ε-polylysine have strong potential for preserving sea bass. © 2022 Society of Chemical Industry.

Facile post-gelation soaking strategy toward low-alkaline konjac glucomannan gels

A facile post-gelation soaking strategy for producing low-alkaline konjac glucomannan (KGM) gels was investigated in this work. The dealkalization kinetics of soaking alkali-induced gels in citric acid (CA) solutions was determined. A comparison of sensory, textural, and water holding properties was made between untreated and post-soaking gels. Post-gelation exposure to acid took less time for lowering the gel pH at higher CA concentrations, eliminated the unattractive flavor of KGM gels and endowed them a higher hardness and breaking force. Comparatively, the whiteness of post-soaking gels was increased by 3.8%-13.1% with volume being decreased by 4.9%-8.6%, while the discrepancies were less apparent after a long-term storage. Low-alkaline gels treated by 4 g/L CA shared similar textural features with conventional KGM gels. Despite the difference in water distribution and water holding capacity of KGM gels, the syneresis of resultant low-alkaline KGM gels was not significantly affected.

Oxidative stability and gelation properties of myofibrillar protein from chicken breast after post-mortem frozen storage as influenced by phenolic compound-pterostilbene

The aim of this study was to elucidate the effects of dietary pterostilbene supplementation on physicochemical changes and gel properties of myofibrillar protein (MP) in chicken when subjected to short-term frozen storage. The results showed that pterostilbene supplementation diminished the oxidation of MP compared to the control, as the carbonyl content was significantly reduced and the loss of sulfhydryl and free amino groups was slowed. Meanwhile, the surface hydrophobicity and insolubility of MP were significantly reduced. FT-IR and endogenous fluorescence spectroscopy analysis indicated that dietary pterostilbene inhibited the unfolding of protein structure and the transition of α-helix to β-sheet structure. The integrity of the protein structure contributed to the gel quality. The strength, whiteness and water-holding capacity (WHC) of MP gels were improved in the pterostilbene treatment group. In terms of microstructure, pterostilbene facilitated the formation of dense and homogeneous gel network structure. In summary, these findings suggest that pterostilbene could be used as a dietary supplement to maintain the structural stability of MP in postmortem chicken breast muscle, allowing for excellent gel functional properties.

Effect of Gum Tragacanth-Sodium Alginate Active Coatings Incorporated With Epigallocatechin Gallate and Lysozyme on the Quality of Large Yellow Croaker at Superchilling Condition

This research was done to investigate the synergistic interactions of the gum tragacanth (GT)–sodium alginate (SA) active coatings, incorporated with epigallocatechin gallate and lysozyme, on the quality of large yellow croaker (Larimichthys crocea) during superchilling storage at −3°C. Results showed that the GT-SA active coatings, containing epigallocatechin gallate [EGCG (E), 0.32% w/v], and lysozyme [LYS (L), 0.32% w/v] have reduced the total viable count, psychrophilic bacteria, and Pseudomonas spp. by about 1.55 log CFU/g, 0.49 log CFU/g, and 1.64 log CFU/g compared to the control at day 35. The GT-SA active coatings containing EGCG and LYS were effective in lowering the formations of off-odor compounds such as total volatile basic nitrogen (TVB-N), malondialdehyde (MDA), and off-favor amino acid (histidine). The solid phase microextraction gas chromatography-mass spectrometer (SPME-GC/MS) was applied to characterize and to quantify the volatile compounds of large yellow croaker samples during superchilling storage, while the relative content of the fishy flavor compounds (including 1-octen-3-ol and acetoin) was significantly reduced in the active coatings treated samples. Furthermore, the GT-SA active coatings containing EGCG and LYS treatments was found to be more effective in retarding the migration of water based on magnetic resonance imaging (MRI) results and in maintaining the organoleptic quality of large yellow croaker in superchilling storage at −3°C according to the sensory evaluation results. The results showed that the GT-SA active coating containing EGCG and LYS was effective to be used as a fish preservative to improve the quality and to prolong the shelf life of large yellow croaker in a superchilling storage for at least 7 days.

Simple Method for Apples' Bruise Area Prediction

From the producers’ point of view, there is no universal and quick method to predict bruise area when dropping an apple from a certain height onto a certain type of substrate. In this study the authors presented a very simple method to estimate bruise volume based on drop height and substrate material. Three varieties of apples were selected for the study: Idared, Golden Delicious, and Jonagold. Their weight, turgor, moisture, and sugar content were measured to determine morphological differences. In the next step, fruit bruise volumes were determined after a free fall test from a height of 10 to 150 mm in 10 mm increments. Based on the results of the research, linear regression models were performed to predict bruise volume on the basis of the drop height and type of substrate on which the fruit was dropped. Wood and concrete represented the stiffest substrates and it was expected that wood would respond more subtly during the free fall test. Meanwhile, wood appeared to react almost identically to concrete. Corrugated cardboard minimized bruising at the lowest discharge heights, but as the drop height increased, the cardboard degraded and the apple bruising level reached the results as for wood and concrete. Contrary to cardboard, the foam protected apples from bruising up to a drop height of 50 mm and absorbed kinetic energy up to the highest drop heights. Idared proved to be the most resistant to damage, while Golden Delicious was medium and Jonagold was least resistant to damage. Numerical models are a practical tool to quickly estimate bruise volume with an accuracy of about 75% for collective models (including all cultivars dropped on each of the given substrate) and 93% for separate models (including single cultivar dropped on each of the given substrate).

Assessment and Feasibility Study of Lemon Ripening Using X-ray Image of Information Visualization

Digital radiography (DR) is a mature technology and has been broadly used in medical diagnosis. Currently, it’s also used for fruit quality inspection in the market. This purpose of the study is to conduct non-destructive experiments for visual comparisons of digital radiography images, further construct visualized grayscale image analysis technology, and analyze the changes in lemon quality and ripening using quantitative statistical methods. The materials used for the experiments were three lemons of different ripening. A general medical X-ray DR system for was used in this study for 2D digital radiography. The medical X-ray DR images were created based on the Digital Imaging and Communications in Medicine (DICOM) standard. Photometric interpretation of monochrome was applied to create multi-layered grayscale images. Then quantitative analyses and comparisons were performed with image matrix structures and grayscale pixel values in the tissues using visualization techniques and statistical methods. After layer segmentation on the radiological images, the correlations between the lemon structures and tissue changes were assessed by using the Kruskal–Wallis test. The results showed that the p values for lemon, fiber, and pulp were all under 0.05, while the peel layer did not exhibit significant change. The pulp layer is the best region for statistical analyses to determine the lemon ripening. In conclusion, this study can provide a solid reference for future quality classification in the agricultural market. The research findings can be referenced for developing computing techniques applied to agricultural inspection, expanding the scope of application of the medical DR technology.

Application of Artificial Neural Network for Prediction of Key Indexes of Corn Industrial Drying by Considering the Ambient Conditions

Uncontrollable ambient conditions are the main factors limiting the self-adaption control of an industrial drying system. To achieve the goal of accurate control of the drying process, the influence of the ambient conditions on the drying behavior should be taken into consideration when modeling the drying process. Present work introduced an industrial drying system with a loading capacity of 50 t, two artificial neural network prediction models with (IANN) and without (OANN) considering the ambient conditions were established using artificial neural network modeling approach. The ambient conditions on the moisture content (MC), exergy efficiency of the heat exchanger (ηex,h) and specific recovered radiant energy (Er) of the drying process were also investigated. The results showed that the ηex,h and Er increase with the increase of ambient temperature while the drying time decrease with the increase of the ambient temperature. The IANN model has a better prediction performance that that of OANN model. An optimal architecture of 9-2-12-3 artificial neuron network model was developed and the best prediction performance of the artificial neural network (ANN) model were found at a training epoch number of 30, and a momentum coefficient of 0.4, where the coefficient of determination of moisture content, exergy efficiency of heat exchanger, and the specific recovered radiant energy, respectively are 0.998, 0.992, and 0.980, indicating that the model has an excellent prediction performance and can be used in engineering practice.

Investigation of the Maturity Changes of Cherry Tomato Using Magnetic Resonance Imaging

The maturity of tomato fruit is normally characterized by external color, and it is often difficult to know when fruit have achieved commercial maturity or become over-mature. The internal structure of tomato fruit changes during development and this study investigates the utility of nondestructive measurement of tomato fruit structure as a function of maturity using magnetic resonance imaging (MRI). The objective of this work is to use analysis of internal tomato fruit structural measurements to characterize maturity. Intact cherry tomato fruit were harvested at six different maturity stages. At each stage of maturity, the internal structure of the fruit was measured using a series of two-dimensional (2D) magnetic resonance (MR) images. Qualitative and quantitative image analyses were performed to correlate internal fruit structure with maturity. Internal structural changes observed in the pericarp region of the tomato fruit are highly correlated with fruit maturity. MR image information combined with classical analysis techniques provides a more complete understanding of structure and physicochemical changes in tomato fruit during maturation. This study demonstrates that MRI is a useful analytical tool to characterize internal changes in agricultural produce as the produce matures. This technique can be applied to almost any agricultural produce to monitor internal physical changes due to external impact, maturity stage, variation in climate, storage time, and condition, or other factors impacting quality.

Developing an Online Measurement Device Based on Resistance Sensor for Measurement of Single Grain Moisture Content in Drying Process

The online measurement of moisture content for grains is an essential technology to realize real-time tracking and control, improve drying quality and reduce energy consumption of the drying process. To improve the measurement accuracy and reliability of the dynamic measurement process as well as expand the application scope of the device, the present work constructed an experimental equipment for determining dynamic resistance characteristics of a single grain. The relations between moisture content and real-time resistance waveform were revealed, and an analytical calculation method of peak value and peak area of waveform was proposed, which correctly revealed the electrical measurement properties of grain. The results demonstrated that the gap width between the electrodes had large influence on the sensor's performance. Moreover, an online measuring device was developed based on the experimental analysis and calculation method, and the test results in both lab and field for different grains showed that online real-time absolute measurement error are within ±0.5% in the varied moisture content (10-35%w.b.) and the temperature (-20-50 °C). The main results and the developed device might provide technical support for developing intelligent grain drying equipment.

Water dynamics changes and protein denaturation in surf clam evaluated by two-dimensional LF-NMR T1-T2 relaxation technique during heating process

Water dynamics and protein denaturation in surf clam during heating were studied by the two-dimensional low-field nuclear magnetic resonance (LF-NMR) T₁-T₂ relaxation technique. A significant change was found for clam around 80 °C and direct visualization of the water state change was provided by the magnetic resonance imaging. Principal components and heatmap analysis revealed that clam treated at 80-100 °C located at different region from those treated at 40-70 °C. The clams heated at 80 °C showed a maximum water holding capability, and significant microstructure change. The differential scanning calorimetry analysis indicated a denaturation of protein when the temperature was over 80 °C. The hardness and chewiness had a maximum value at 80 and 70 °C, respectively. The color parameter L* showed a significant increase when temperature was over 80 °C. This demonstrated that the T₁-T₂ technique has potential in evaluating water dynamics for surf clam during heating.

Preservative Effects of Gelatin Active Coating Containing Eugenol and Higher CO2 Concentration Modified Atmosphere Packaging on Chinese Sea bass (Lateolabrax maculatus) during Superchilling (-0.9 °C) Storage

The purpose of this research was to explore the fresh keeping effect of modified atmosphere packaging (MAP) with different gas ratios combined with gelatin active coatings containing eugenol on Chinese sea bass stored at −0.9 °C for 36 days. The results showed that MAP3 (60% CO₂/10% O₂/30% N₂), together with gelatin active coatings containing eugenol, could prevent water loss, which maintained high field NMR, MRI, and organoleptic evaluation results. This hurdle technology could also effectively delay the bacterial reproduction, protein degradation, and alkaline accumulation, so it showed the lowest K value, total volatile basic nitrogen, free amino acids, total viable count, Pseudomonas spp., and H₂S-producing bacteria, which better maintain the quality of sea bass.

Biogenic Amines Formation Mechanism and Determination Strategies: Future Challenges and Limitations

The evolution in foodstuff-monitoring processes has increased the number of studies on biogenic amines (BAs), in recent years. This trend with future perspective needs to be assembled to address the associated health risks. Thus, this study aims to cover three main aspects of BAs: (i) occurrence, physiology, and toxicological effects, most probable formation mechanisms and factors controlling their growth; (ii) recent advances, strategies for determination, preconcentration steps, model technique, and nature of the matrix; and (iii) milestone, limitations with existing methodologies, future trends, and detailed expected developments for clinical use and on-site ultra-trace determination. The core of the ongoing review will discuss recent trends in pre-concentration toward miniaturization, automation, and possible coupling with electrochemical techniques, surface-enhanced Raman scattering, spectrofluorimetry, and lateral flow protocols to be exploited for the development of rapid, facile, and sensitive on-site determination strategies for BAs.

Low-Field NMR and MRI to Analyze the Effect of Edible Coating Incorporated with MAP on Qualities of Half-Smooth Tongue Sole (Cynoglossus Semilaevis Günther) Fillets during Refrigerated Storage

Nondestructive and fast measurement and characterization of fish is highly desired during various processing treatments. This research investigated the effectiveness of low field LF-NMR and MRI as fast monitoring techniques to estimate the qualities of half-smooth tongue sole fillets treated with edible coating combined with modified atmosphere packaging during refrigeration. T2 relaxation spectra showed three peaks representing bound water (T21), immobile water (T22), and free water (T23), respectively. pT22 accounted for the largest proportion of three types of water, followed by pT23. The weighted MRI provided the internal structure information associated with different samples, indicting the combination of edible coating and MAP (70% CO2 + 30% N2) is the best performance in the maintenance of qualities and freshness of HTS fillets. All results demonstrated that the combination of LF-NMR and MRI as fast and nondestructive methods have great potential to monitor qualities deterioration and predict shelf life in of HTS fillets during refrigerated storage.

Dynamic Water Mobility in Sea Cucumber (Stichopus japonicas) During Drying Process Assessed by LF-NMR and MRI in situ

The purpose of this study is to elucidate the water dynamics in sea cucumber (Stichopus japonicas) during drying processin situby the fast and non-destructive low field nuclear magnetic resonance (LF-NMR) and magnetic resonance imaging (MRI) methods.T2relaxation spectra in three-dimensional (3D) color map surface image from LF-NMR showed three main peaks assigned to bound water with relaxation time less than 2 ms, immobilized water in the range of 15–150 ms and extra-collagen fibrillar bulk water or free water adhered onto the sea cucumber with the longest relaxation time 200–1600 ms. The water dynamics in sea cucumber during drying process was clearly observed from the 3D color map surface image. Significant correlations between the LF-NMRT2parameters (ATotal, A23andT23) and TPA parameters were observed, demonstrating that LF-NMR might be a complementary technique in monitoring the textural properties of sea cucumber during drying process.