This work presents the use of multiple techniques (i.e., physicochemical and spectral) applied to harvested coffee cherries for the postharvest classification of the maturity stage. The moisture content (MC), total soluble solids (TSS), bulk density, fruits’ hardness, CIEL*a*b parameters and the dielectric spectroscopy methods were applied on coffee cherries at seven maturity stages. These maturity stages were assessed according to the days after flowering (DAF) and the physical appearance as traditionally performed by growers. An increase of the green-to-red ratio (i.e., a*) parameter was perceived, accompanied by a monotonic response for the hardness, TSS and bulk density with a maximum moisture content at stage 5. In the case of the dielectric spectroscopy technique, the loss parameter presented higher losses for unripe stages at the ionic conduction region. To compare the individual performance of each of the techniques, three machine learning methods were used: random forest (RF), support vector machine (SVM) and k-nearest neighbours (k-NN). The meta-parameters for these techniques were optimized for each case to achieve the best performance possible. Furthermore, as the dielectric response is of spectral nature, recursive feature selection was applied and the 500MHz to 1.3 GHz frequency range selected for the task. The highest performance was obtained for the colorimetric (75.1%) and hardness (72.5%) responses, while the lowest was obtained for the moisture content (45.5%). The dielectric spectroscopy response presented a promising response (56.8%), that achieved a clear separation of unripe from ripe stages, except for stage 5 in which some of the samples were classified as stage 2. Most techniques studied are compatible with field conditions, and the dielectric technique shows potential to be transferred based on availablesoftware-radio defined platforms. Key words: Dielectric spectroscopy; Coffee maturity; Postharvest classification; Physicochemical analysis.

Dielectric properties (DP: relative permittivity and loss factor) and electrical conductivity are important parameters for evaluating the microwave penetration depth and designing applicators for pasteurization processes. In this context, generalized equations that can predict the DP of a group of food products as a function of their characteristics are useful. The dielectric behaviours of eight citrus fruit juices (Pera, Lima, and Navel oranges, Ponkan tangerine, Murcott tangor, Mediterranean mandarin, Sicilian lemon, and Persian lime) and three Pera/Lima blends (25, 50, 75%) for temperatures between 0 and 90 °C and frequency between 500 and 3000 MHz were studied. The results were correlated with temperature at frequencies of 915 and 2450 MHz. It was possible to quantify the ionic and dipolar contributions. DPs were modelled based on the behaviour of pure water in a semiempirical approach using correction factors, which were correlated with temperature and juice physicochemical characteristics (pH, Brix, conductivity). Polynomial regressions can successfully predict relative permittivity with mean absolute errors of 0.49±0.35% and 0.58±0.48% and the loss factor with errors of 4.1±3.9% and 2.8±2.3% at 915 and 2450 MHz, respectively, for juices with Brix/acid ratio between 1.26 and 29.9.

A prototype device based on a modified domestic microwave oven for liquid food products pasteurization is presented. This novel design has a coiling glass pipe adapted inside a microwave cavity to allow liquid continuous flow, in which several temperature optical sensors based on Fiber Bragg Grating were installed to measure, by means of contact, the circulating liquid temperature in the pipe, while the oven is on, to obtain the profile temperature as a function of time at different pipe points. The temperatures at liquid input and output were also measured with thermocouples. This device was tested to establish how well it may perform using different standardized liquids with well-known physicochemical and dielectric properties, such as water, water with dissolved sugars, water with dissolved salts, and water with dissolved sugars and salts. It could be observed that the maximum temperature reached was 90 °C for distilled water, 80 °C for water with dissolved salts, 60 °C for water with dissolved sugars and 80 °C for water with dissolved sugars and salts, showing that these data were in agreement with previous results in the literature. This type of device would be potentially useful to establish the device’s efficiency in terms of retention time, energy consumption, and volume of processed liquid, thus, broadening the use of this microwave heating technology with several types of liquid substances.