An improved and fast UHPLC-PDA methodology for determination of L-ascorbic and dehydroascorbic acids in fruits and vegetables: evaluation of degradation rate during storage

This study provides a versatile validated method to determine the total vitamin C content, as the sum of the contents of L-ascorbic acid (L-AA) and dehydroascorbic acid (DHAA), in several fruits and vegetables and its degradability with storage time. Seven horticultural crops from two different origins were analyzed using an ultrahigh-performance liquid chromatographic–photodiode array (UHPLC-PDA) system, equipped with a new trifunctional high strength silica (100% silica particle) analytical column (100 mm×2.1 mm, 1.7 μm particle size) using 0.1% (v/v) formic acid as mobile phase, in isocratic mode. This new stationary phase, specially designed for polar compounds, overcomes the problems normally encountered in HPLC and is suitable for the analysis of large batches of samples without L-AA degradation. In addition, it proves to be an excellent alternative to conventional C18 columns for the determination of L-AA in fruits and vegetables. The method was fully validated in terms of linearity, detection (LOD) and quantification (LOQ) limits, accuracy, and inter/intraday precision. Validation experiments revealed very good recovery rate of 96.6±4.4% for L-AA and 103.1±4.8 % for total vitamin C, good linearity with r2-values >0.999 within the established concentration range, excellent repeatability (0.5%), and reproducibility (1.6%) values. The LOD of the method was 22 ng/mL whereas the LOQ was 67 ng/mL. It was possible to demonstrate that L-AA and DHAA concentrations in the different horticulture products varied oppositely with time of storage not always affecting the total amount of vitamin C during shelf-life. Locally produced fruits have higher concentrations of vitamin C, compared with imported ones, but vegetables showed the opposite trend. Moreover, this UHPLC-PDA methodology proves to be an improved, simple, and fast approach for determining the total content of vitamin C in various food commodities, with high sensitivity, selectivity, and resolving power within 3 min of run analysis.

Using Neo4J geospatial data storage and integration

Online geographic-databases have been growing increasingly as they have become a crucial source of information for both social networks and safety-critical systems. Since the quality of such applications is largely related to the richness and completeness of their data, it becomes imperative to develop adaptable and persistent storage systems, able to make use of several sources of information as well as enabling the fastest possible response from them. This work will create a shared and extensible geographic model, able to retrieve and store information from the major spatial sources available. A geographic-based system also has very high requirements in terms of scalability, computational power and domain complexity, causing several difficulties for a traditional relational database as the number of results increases. NoSQL systems provide valuable advantages for this scenario, in particular graph databases which are capable of modeling vast amounts of inter-connected data while providing a very substantial increase of performance for several spatial requests, such as finding shortestpath routes and performing relationship lookups with high concurrency. In this work, we will analyze the current state of geographic information systems and develop a unified geographic model, named GeoPlace Explorer (GE). GE is able to import and store spatial data from several online sources at a symbolic level in both a relational and a graph databases, where several stress tests were performed in order to find the advantages and disadvantages of each database paradigm.