Monitoring of fresh-cut Valerianella locusta Laterr. shelf life by electronic nose and VIS-NIR spectroscopy

Juice Quality Evaluation with Multisensor Systems-A Review

E-nose and e-tongue are advanced technologies that allow for the fast and precise analysis of smells and flavours using special sensors. Both technologies are widely used, especially in the food industry, where they are implemented, e.g., for identifying ingredients and product quality, detecting contamination, and assessing their stability and shelf life. Therefore, the aim of this article is to provide a comprehensive review of the application of e-nose and e-tongue in various industries, focusing in particular on the use of these technologies in the fruit and vegetable juice industry. For this purpose, an analysis of research carried out worldwide over the last five years, concerning the possibility of using the considered multisensory systems to test the quality and taste and aroma profiles of juices is included. In addition, the review contains a brief characterization of these innovative devices through information such as their origin, mode of operation, types, advantages and disadvantages, challenges and perspectives, as well as the possibility of their applications in other industries besides the juice industry.

Effects of NaCl and CaCl2 as Eustress Factors on Growth, Yield, and Mineral Composition of Hydroponically Grown Valerianella locusta

Corn salad (Valerianella locusta) is a popular winter salad, cultivated as an ingredient for ready-to-eat salads. The application of mild salinity stress (eustress) can increase the flavor and reduce the nitrate content of certain crops but, at the same time, a wrong choice of the eustress type and dose can negatively affect the overall productivity. In this research, the effects of different isosmotic salt solutions, corresponding to two different electrical conductivity (EC) levels, were investigated on the yield and mineral composition of hydroponically grown Valerianella locusta "Elixir". Five nutrient solutions (NS) were compared, including a basic NS used as the control, and four saline NS were obtained by adding to the basic NS either NaCl or CaCl₂ at two rates each, corresponding to two isosmotic salt levels at a low and high EC level. Corn salad proved moderately susceptible to long-term salinity stress, suffering growth losses at both low and high EC levels of saline solution, except from the low NaCl treatment. Hence, it appears that mild salinity stress induced by NaCl could be employed as an eustress solution and corn salad could be cultivated with low-quality irrigation water (20 mM NaCl) in hydroponic systems.

VIS-NIR Modeling of Hydrangenol and Phyllodulcin Contents in Tea-Hortensia (Hydrangea macrophylla subsp. serrata)

Hyperspectral data are commonly used for the fast and inexpensive quantification of plant constituent estimation and quality control as well as in research and development applications. Based on chemical analysis, different models for dihydroisocoumarins (DHCs), namely hydrangenol (HG) and phyllodulcin (PD), were built using a partial least squares regression (PLSR). While HG is common in Hydrangea macrophylla, PD only occurs in cultivars of Hydrangea macrophylla subsp. serrata, also known as ‘tea-hortensia’. PD content varies significantly over the course of the growing period. For maximizing yield, a targeted estimation of PD content is needed. Nowadays, DHC contents are determined via UPLC, a time-consuming and a destructive method. In this research article we investigated PLSR-based models for HG and PD using three different spectrometers. Two separate trials were conducted to test for model quality. Measurement conditions, namely fresh or dried leaves and black or white background, did not influence model quality. While highly accurate modeling of HG and PD for single plants was not possible, the determination of the mean content on a larger scale was successful. The results of this study show that hyperspectral modeling as a decision support for farmers is feasible and provides accurate results on a field scale.

Production and Characterization of a Novel Low-Sugar Beverage from Red Jujube Fruits and Bamboo Shoots Fermented with Selected Lactiplantibacillus plantarum

Red jujube fruits and bamboo shoots are rich in many nutrients and have the advantage of high yield in China. However, the storage of fresh fruits is difficult, and there are no fermented products using both as raw materials. In order to develop the two raw materials into novel products and improve their nutritional value, this study reports the production and characterization of a beverage via fermentation of red jujube fruits and bamboo shoots with Lactiplantibacillus plantarum. L. plantarum TUST-232 was selected as the starter from several different strains by comparing pH value and the number of viable cells, which reached 8.91 log CFU/mL in the beverage fermented for 14 h at 37 °C with 0.3% inoculation. After fermentation, the beverage showed improvement in the contents of several nutrients and antioxidant indices, with a decrease of 44.10% in sucrose content, along with increases of 11.09%, 12.30%, and 59.80% in total phenolic content, total antioxidant capacity, and superoxide anion scavenging ability, respectively. These results indicate that L. plantarum fermentation of red jujube fruits and bamboo shoots could be an effective way to develop a new beverage with high nutritional value, high antioxidant capacity, and high dietary fiber content. This research provided experimental support for the development of new fermentation products with the functions of improving health and body functions.

Influence of Two Innovative Packaging Materials on Quality Parameters and Aromatic Fingerprint of Extra-Virgin Olive Oils

The performance of two innovative packaging materials was investigated on two Sardinian extra-virgin olive oils (Nera di Gonnos and Bosana). In particular, a transparent plastic film loaded with a UV-blocker (packaging B) and a metallized material (packaging C) were compared each other and to brown-amber glass (packaging A). During accelerated shelf-life tests at 40 and 60 °C, the evolution of quality parameters (i.e., acidity, peroxide value, K₂₇₀, and phenolic content) was monitored, together with the aromatic fingerprint evaluated by electronic nose. Packaging B resulted in the best-performing material in protecting oil from oxidation, due to its lower oxygen transmission rate (0.1 ± 0.02 cm³/m² 24 h) compared to packaging C (0.23 ± 0.04 cm³/m² 24 h). At the end of storage, phenolic reduction was on average 25% for packaging B and 58% for packaging C, and the aromatic fingerprint was better preserved in packaging B. In addition, other factors such as the sanitary status of the olives at harvesting and the storage temperature were demonstrated to have a significant role in the shelf life of packaged extra-virgin olive oil.

Identifying Freshness of Spinach Leaves Stored at Different Temperatures Using Hyperspectral Imaging

Spinach is prone to spoilage in the course of preservation. Spinach leaves stored at different temperatures for different durations will have varying degrees of freshness. In order to monitor the freshness of spinach leaves during storage, a rapid and non-destructive method—hyperspectral imaging technology—was applied in this study. Visible near-infrared reflectance (Vis-NIR) (380–1030 nm) and near-infrared reflectance (NIR) (874–1734 nm) hyperspectral imaging systems were used. Spinach leaves preserved at different temperatures with different durations (0, 3, 6, 9 days at 4 °C and 0, 1, 2 days at 20 °C) were studied. Principal component analysis (PCA) was adopted as a qualitative analysis method. The second-order derivative spectra were utilized to select effective wavelengths. Partial least squares discriminant analysis (PLS-DA), support vector machine (SVM), and extreme learning machine (ELM) were used to build models based on full spectra and effective wavelengths. All three models achieved good results, with accuracies above 92% for both Vis-NIR spectra and NIR spectra. ELM obtained the best results, with all accuracies reaching 100%. The overall results indicate the possibility of the freshness identification of spinach preserved at different temperatures for different durations using two kinds of hyperspectral imaging systems.

Horseradish peroxidase-mediated synthesis of an antioxidant gallic acid-g-chitosan derivative and its preservation application in cherry tomatoes

Owing to their good solubility and film-forming properties, phenolic acid-g-chitosan derivatives can be used for preservation of fruits and vegetables. However, the chemical synthesis used for the preparation of these derivatives poses a great challenge to food safety. In this study, a method involving horseradish peroxidase catalysis was used to prepare a gallic acid-g-chitosan derivative. The grafting mechanism was studied. Then, the derivative's ability to scavenge free radicals and its preserving application in cherry tomatoes were evaluated. The results indicated that the reaction for horseradish peroxidase catalysis occurred between the amino group of chitosan and the carboxyl group of gallic acid. After enzymatic grafting, the gallic acid-g-chitosan derivative possessed excellent antioxidant abilities in scavenging DPPH, hydroxyl, and superoxide anion radicals. When the derivative was used for the preservation of cherry tomatoes, the results showed that it could effectively protect the ascorbate-glutathione cycle and antioxidant enzyme system of cherry tomatoes and inhibit enzymatic browning. In addition, since this derivative delayed the postharvest senescence of cherry tomatoes, the aroma compounds remain relatively constant throughout the storage period.

The prediction of food additives in the fruit juice based on electronic nose with chemometrics

Food additives are added to products to enhance their taste, and preserve flavor or appearance. While their use should be restricted to achieve a technological benefit, the contents of food additives should be also strictly controlled. In this study, E-nose was applied as an alternative to traditional monitoring technologies for determining two food additives, namely benzoic acid and chitosan. For quantitative monitoring, support vector machine (SVM), random forest (RF), extreme learning machine (ELM) and partial least squares regression (PLSR) were applied to establish regression models between E-nose signals and the amount of food additives in fruit juices. The monitoring models based on ELM and RF reached higher correlation coefficients (R²s) and lower root mean square errors (RMSEs) than models based on PLSR and SVM. This work indicates that E-nose combined with RF or ELM can be a cost-effective, easy-to-build and rapid detection system for food additive monitoring.

Phytochemical Composition and Antitumor Activities of New Salad Greens: Rucola (Diplotaxis tenuifolia) and Corn Salad (Valerianella locusta)

D. tenuifolia and V. locusta, two greens, were analyzed for active compounds and antitumor actions on colorectal cancer cells. Phenolics were determined by UHPLC-Orbitrap-MS; carotenoids and glucosinolates by HPLC-MS; and sterols and fatty acids by gas-liquid chromatography (GLC). For antitumor effects, the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and lactate dehydrogenase (LDH) tests were run on HT-29 colorectal cancer cells, and in CCD-18 untransformed enterocyte cells. Six main carotenoids were identified in both vegetables, while total carotenoids accounted for 3520 and 2970 μg · g(-1) dry weight in D. tenuifolia and V. locusta, respectively. Six phenolics were detected in D. tenuifolia (68,600 μg · g(-1) dry weight) and five in V. locusta (139,000 μg · g(-1) dry weight). Three glucosinolates (GSL) were found in D. tenuifolia (1960 μg · g(-1) dry wt. total). Low-polarity extracts from V. locusta and D. tenuifolia showed IC50 ~ 150 and ~200 μg · mL(-1) on HT-29 cells, while both plants lacked actions on CCD-18 cells. V. locusta inhibited HT-29 cancer cells viability more efficiently than D. tenuiofolia, but induced less cytotoxicity. This work highlights the importance of functional foods for colorectal cancer prevention.

Early detection of Zygosaccharomyces rouxii--spawned spoilage in apple juice by electronic nose combined with chemometrics

Spoilage spawned by Zygosaccharomyces rouxii can cause sensory defect in apple juice, which could hardly be perceived in the early stage and therefore would lead to the serious economic loss. Thus, it is essential to detect the contamination in early stage to avoid costly waste of products or recalls. In this work the performance of an electronic nose (e-nose) coupled with chemometric analysis was evaluated for diagnosis of the contamination in apple juice, using test panel evaluation as reference. The feasibility of using e-nose responses to predict the spoilage level of apple juice was also evaluated. Coupled with linear discriminant analysis (LDA), detection of the contamination was achieved after 12h, corresponding to the cell concentration of less than 2.0 log 10 CFU/mL, the level at which the test panelists could not yet identify the contamination, indicating that the signals of e-nose could be utilized as early indicators for the onset of contamination. Loading analysis indicated that sensors 2, 6, 7 and 8 were the most important in the detection of Z. rouxii-contaminated apple juice. Moreover, Z. rouxii counts in unknown samples could be well predicted by the established models using partial least squares (PLS) algorithm with high correlation coefficient (R) of 0.98 (Z. rouxii strain ATCC 2623 and ATCC 8383) and 0.97 (Z. rouxii strain B-WHX-12-53). Based on these results, e-nose appears to be promising for rapid analysis of the odor in apple juice during processing or on the shelf to realize the early detection of potential contamination caused by Z. rouxii strains.

Fuji apple storage time rapid determination method using Vis/NIR spectroscopy

Fuji apple storage time rapid determination method using visible/near-infrared (Vis/NIR) spectroscopy was studied in this paper. Vis/NIR diffuse reflection spectroscopy responses to samples were measured for 6 days. Spectroscopy data were processed by stochastic resonance (SR). Principal component analysis (PCA) was utilized to analyze original spectroscopy data and SNR eigen value. Results demonstrated that PCA could not totally discriminate Fuji apples using original spectroscopy data. Signal-to-noise ratio (SNR) spectrum clearly classified all apple samples. PCA using SNR spectrum successfully discriminated apple samples. Therefore, Vis/NIR spectroscopy was effective for Fuji apple storage time rapid discrimination. The proposed method is also promising in condition safety control and management for food and environmental laboratories.