Browsing by Subject "Raw"

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    Effect of industrial processing on amino acid content of broccoli
    (Wiley, Society of Chemical Industry, 2001) Murcia Tomás, María Antonia; López Ayerra, Beatriz; Martínez Tomé, Magdalena; García Carmona, Francisco; Tecnología de Alimentos, Nutrición y Bromatología
    The levels of amino acids in broccoli stems and florets before and after various blanching times (in the case of freezing) and after bottling have been studied to elucidate to what extent nutrient quality is affected by industrial processing. The following amino acids (mg kg-1 fresh weight) were identified by ion exchange chromatography in raw broccoli florets: glutamine (1338), proline (732), asparagine (578), valine (310), arginine (296), isoleucine (204), threonine (169), leucine (166), phenylalanine (159), aspartic acid (140), lysine (127), alanine (122), tyrosine (105), S-methylcysteine (96), histidine (89), ornithine (59), glutamic acid (44), -y-aminobutyric acid (31), glycine (11) and serine (0.2). Raw stems contained the same amino acids but at lower levels (p < 0.05). The levels of all these amino acids fell during both industrial processes studied (bottling and freezing after blanching for 60, 90, 120 and 150 s), particularly in the frozen samples (losses of 50-70% in the florets and 20-50% in the stems). In summary, losses of broccoli amino acids were lower if blanching times were kept short. The optimal blanching time at 94 C for florets and stems intended for freezing was 90 s, and this did not result in any great loss of nutritional value related to amino acid content. Bottled florets had greater nutritional value than those frozen after being exposed to the longest blanching times (120 and 150 s).
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    Open Access
    From big data mining to technical sport reports: the case of inertial measurement units
    (BMJ Journals, 2025-01-21) Rojas-Valverde ‍, Daniel; Gómez-Carmona, Carlos D; Gutiérrez-Vargas, Randall; Pino Ortega, José; Actividad Física y Deporte
    The inertial measurement units (IMU) are instruments used to quantify the external load of athletes; they are increasingly common in assessing team and individual sports. This type of instruments has several sensors, such as accelerometers, gyroscopes and magnetometers; this allows access to a large amount of information and analysis possibilities. Due to the complexity of synthesising this data, it is necessary to create a flow for collecting, analysing and presenting the collected data in a simple way and present it as quickly as possible to the technical staff. This report aims to present new methods of reduction of the data and propose a new approach method for the analysis of the IMU’s outcomes.