Enzymatic obtainment of pectin and pectic oligosaccharides from artichoke by-products. Structural characterization and functional evaluation through machine learning

Tesis Doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Ciencias, Departamento de Química Física Aplicada. Fecha de lectura: 22-11-201

Applications of Instrumental Methods for Food and Food By-Products Analysis

The analysis of food and food by-products is a particularly important topic dealing with the development and application of various analytical procedures and methods determining the properties and safety of food and food constituents. It is an important tool not only for defining food quality but also for supporting the investigation of new food products and technologies. The continuous development of methodology and access to modern research equipment enable detailed research on the composition, structure, physicochemical properties, thermal characteristics, and stability of food products and, recently, also byproducts of the food industry, which are potentially a source of bioactive compounds and currently present little commercial value and are mostly disposed of as an industrial waste. It is imperative to identify the properties and potential applications of food by-products, which would fit in with current trends in circular ecology. Taking the aforementioned reasons into account, it is important to present procedures and instrumental analytical techniques and methods commonly used to analyze food and food processing byproducts and to discuss their application in food research to detect and characterize specific food components of significance to food science and technology, such as lipids, proteins, and carbohydrates

Prediction of soluble solid content of starfruit using spectral imaging combined with partial least squares and support vector regression

Spectral imaging technique such as hyperspectral and multispectral imaging is a combination of imaging and spectroscopy. This powerful technique can provide samples of spectral images, which can be used to analyze a number of fruit properties. The aim of this study is to develop calibration or predictive model for determining soluble solid content (SSC) of starfruit samples based on their spectral images. Partial least squares (PLSR) and support vector regression (SVR) techniques were applied to build the relationship between the mean spectral data and the reference value. The mean spectral data was extracted from spectral images of each starfruit samples. The simple template for region of interest (ROI) selection and five optimal wavelengths (565.2, 677.2, 736, 873.2 and 943.2 nm) as proposed in previous study were used for extraction of the mean spectral data. The result showed that the calibration model with PLSR and SVR had better performance than the previous study. Moreover, the calibration model with SVR was the best performance for prediction of SSC value of starfruit

SPATIAL TRANSFORMATION PATTERN DUE TO COMMERCIAL ACTIVITY IN KAMPONG HOUSE

ABSTRACT Kampung houses are houses in kampung area of the city. Kampung House oftenly transformed into others use as urban dynamics. One of the transfomation is related to the commercial activities addition by the house owner. It make house with full private space become into mixused house with more public spaces or completely changed into full public commercial building. This study investigate the spatial transformation pattern of the kampung houses due to their commercial activities addition. Site observations, interviews and questionnaires were performed to study the spatial transformation. This study found that in kampung houses, the spatial transformation pattern was depend on type of commercial activities and owner perceptions, and there are several steps of the spatial transformation related the commercial activity addition. Keywords: spatial transformation pattern; commercial activity; owner perception, kampung house; adaptabilit