Shifts in the Bacterial Community Related to Quality Properties of Vacuum-Packaged Peeled Potatoes during Storage

Bacterial diversity, community structure and function in association of potato scabby tubers during storage in northern Thailand

Potato scab is a common potato tuber disease that affects quality and cost in the marketplace, shortening storage, and increasing the chance for secondary infection. The tubers with disease severity of 1 to 4 are accepted and stored in potato storage for cheap selling in Thailand. However, there are few studies of the bacterial community of the scabby tuber during storage. Thus, we aim to elucidate the diversity, structure, and function of the bacterial community of 30-day storage potato scabby tubers stored in different temperatures using 16S amplicon metagenomic sequencing. Bacterial communities of storage potato scabby tubers (Spunta cultivar) collected from different storage temperatures, 4 °C (MEP1) and 6 °C (MEP2), were characterized using 16S rRNA amplicon metagenomic sequencing. The alpha-diversity abundance in the bacteriome of the scabby tubers stored at 6 °C was higher than in those stored at 4 °C. Actinobacteria (34.7%) was a dominant phylum in MEP1, while Proteobacteria (39.9%) was predominant in MEP2. The top 10 genera of both communities were Rhizobium group, Streptomyces, Pectobacterium, Ruminococcus, Cellulomonas, Promicromonospora, Prevotella, Enterobacter, Pedobacter, and Paenarthrobacter. Moreover, functional profile prediction of both communities reveals essential genes in the pathosystem: nos, bglA, and cebEFG-msiK for potato scab disease and phc and peh operons for rot disease. Our findings are the first study to explore details of the bacteriome of the accepted potato scabby tubers for selling during storage in Thailand and strongly indicate that although potatoes were stored at low temperatures, diseases still occur by secondary pathogens.

Microbial community succession and their relationship with the flavor formation during the natural fermentation of Mouding sufu

Mouding sufu, a traditional fermented soybean product in China, has been recognized by the public in the southwestern regions of China. To reveal the microbial community succession and their relationship with the flavor formation during the natural fermentation of Mouding sufu, microbial community, non-volatile flavor compounds and volatile flavor compounds were analyzed by high-throughput sequencing, high-performance liquid chromatography, gas chromatography ion migration spectroscopy, respectively. The results showed that Lactobacillus and Klebsiella were the most abundant bacterial genus, whereas the main fungal genera were unclassified-f-Dipodascaeae and Issatchenkia. In addition, Glutamic acid, Aspartic acid, Alanine, Valine, Lysine, Histidine, lactic acid, succinic acid, and acetic acid were the main non-volatile flavor substances. Furthermore, the taste activity values of glutamic acid, aspartic acid and lactic acid reached 132, 68.9, 18.18 at H60, respectively, meaning that umami and sour were the key taste compounds. Simultaneously, ethyl 3-methylbutanoate-M, ethyl propanoate, methyl 2-methylbutanoate, ethyl 2-methylbutanoate, ethyl 3-methylbutanoate-D, ethyl isobutyrate, linalool-M, linalool-D, cis-4-heptenal, 2-methylpropanal were the characteristic volatile flavor of Mouding sufu. Finally, correlation analysis showed that g__Erwinia and g__Acremonium correlated with most of the key aroma compounds. 20 bacteria and 21 fungi were identified as core functional microbe for Mouding sufu production.

Effect of Ultrasound Combinated with Sodium Hypochlorite Treatment on Microbial Inhibition and Quality of Fresh-Cut Cucumber

The influence of ultrasound combined with sodium hypochlorite (US-NaClO) treatment on microorganisms and quality of fresh-cut cucumber during storage were investigated. Ultrasound (400 W, 40 kHz, US: 5, 10 and 15 min) and sodium hypochlorite (NaClO: 50, 75, 100 ppm) were used to treat fresh-cut cucumber in a single or combined treatment and stored at 4 °C for 8 days and analyzed for texture, color and flavor. The results showed that US-NaClO treatment had a synergistic effect on the inhibition of microorganisms during storage. It could significantly reduce (p < 0.05) the number of microorganisms by 1.73 to 2.17 log CFU/g. In addition, US-NaClO treatment reduced the accumulation of malondialdehyde (MDA) during storage (4.42 nmol/g) and water mobility, and maintained the integrity of the cell membrane, delayed the increase of weight loss (3.21%), reduced water loss, thus slowing down the decline of firmness (9.20%) of fresh-cut cucumber during storage. The degradation of chlorophyll (6.41%) was reduced to maintain the color of freshly cut cucumbers. At the same time, US-NaClO could maintain the content of aldehydes, the main aromatic substance of cucumber, and reduced the content of alcohols and ketones during storage. Combined with the electronic nose results, it could maintain the cucumber flavor at the end of the storage period and reduce the odor produced by microorganisms. Overall, US-NaClO was helpful to inhibit the growth of microorganisms during storage, improve the quality of fresh-cut cucumber.

Determining the shelf life and quality changes of potatoes (Solanum tuberosum) during storage using electronic nose and machine learning

The activities of alpha-amylase, beta-amylase, sucrose synthase, and invertase enzymes are under the influence of storage conditions and can affect the structure of starch, as well as the sugar content of potatoes, hence altering their quality. Storage in a warehouse is one of the most common and effective methods of storage to maintain the quality of potatoes after their harvest, while preserving their freshness and sweetness. Smart monitoring and evaluation of the quality of potatoes during the storage period could be an effective approach to improve their freshness. This study is aimed at assessing the changes in the potato quality by an electronic nose (e-nose) in terms of the sugar and carbohydrate contents. Three potato cultivars (Agria, Santé, and Sprite) were analyzed and their quality variations were separately assessed. Quality parameters (i.e. sugar and carbohydrate contents) were evaluated in six 15-day periods. The e-nose data were analyzed by means of chemometric methods, including principal component analysis (PCA), linear data analysis (LDA), support vector machine (SVM), and artificial neural network (ANN). Quadratic discriminant analysis (QDA) and multivariate discrimination analysis (MDA) offer the highest accuracy and sensitivity in the classification of data. The accuracy of all methods was higher than 90%. These results could be applied to present a new approach for the assessment of the quality of stored potatoes.