Cristina Tortia

Modelling and Control of Steam Soil Disinfestation Processes

Abstract Soil disinfestation by steam is an agricultural technique that recently has been attracting growing interest for its low ecological impact. The process represents a viable alternative to methyl bromide, which will soon be banned in many countries. However, high fuel costs render the treatment only economically feasible for high-profit cultures. In this paper, a predictive control structure is presented, aimed at reducing the fuel consumption and optimising the treatment duration. The controller is based on a multiple linear parameter varying switching dynamic model that describes the soil temperature at different depths during sheet steam disinfestation. This fairly new approach allows the construction of simple models, thus overcoming the complexity introduced by physical equations.

Grey-box models for steam soil disinfestation simulation

Agricultural and biological processes often involve complex phenomena that depend not only on time but also on other independent variables, like spatial coordinates. These processes are intrinsically distributed parameter systems whose modelling requires the adoption of (non linear) partial differential equation. Due to their complexity these models often involve parameters difficult to be estimated, require time-consuming computations and could be not suitable for control purposes.In this paper, a new model structure for the simulation of steam soil disinfestation processes has been developed. The proposed model is based on a grey-box structure and it is mainly constituted by a couple of lumped linear parameter varying (LPV) switching model.Attention is focused on the simulation of sheet steaming soil disinfestation processes that are nowadays gaining growing interest as an ecological alternative to methyl bromide fumigation. To this extent, the model has been identified and validated using real data collected during greenhouse and open field steam treatments.

PREDICTIVE CONTROL FOR THE OPTIMIZATION OF STEAM SOIL DISINFESTATION

Abstract Soil disinfestation by steam is an agricultural technique that is nowadays attracting growing interest for its low ecological impact and could therefore become a viable alternative to methyl bromide, that will soon banned. The current main limitation of this treatment is due to the cost of the fuel used to generate the steam. In this paper, we present a control strategy that allows to minimize fuel consumption by optimizing the time of steam soil exposure. The effectiveness of the proposed techniques has been tested using real data collected from experiments performed in a farm in the Liguria Italian region.

Computer vision for laboratory quality control on frozen fruit

The appropriate amount of antioxidant compounds added in frozen light-flesh cut fruit production process is usually estimate evaluating colour changes, in particular by measuring the minimum time before browning phenomena occur. This parameter is assessed by visual inspections performed by trained operators: a time consuming and strongly subjective procedure. The development of a Computer Vision System (CVS) for quality control in frozen fruit slice is presented in this paper. An algorithm to detect and measure browned area on fruit slices was implemented in order to describe colour changes evolution. The red component of browned areas is emphasized by an adequate linear combination of RGB colour channels of digital images, and an entropy-based automatic segmentation is applied to the obtained high contrast grey-scale image. This approach is not based on colour measurement of samples by the CVS, avoiding the colour calibration phase. Antioxidant solutions with different concentrations were applied in order to obtain different browning times and evaluate algorithm performances. Results obtained with the CVS strongly fit with visual inspections performed by trained operators, showing the reliability of the method for this specific application.

Temperature and position effect on readability of passive UHF RFID labels for beverage packaging

The radio frequency identification (RFID) of food items improves production process efficiency as well as optimises the management of the monitoring and the logistics along the production chain (Barge et al., 2014). Moreover, interest in UHF RFID tags adoption is growing in particular applications such as anti-counterfeiting systems. The readability of passive UHF RFID tags is well known to be critical when applied to products at high water content. Nevertheless, the effect on readability of solutions of water and other organic (e.g. ethanol, sugars, organic acids) or inorganic (salts) compounds, which are typical of food and beverage composition, has not yet been studied. Furthermore, as in the case of beverages that must be chilled for their conservation (i.e. fruit juice, fresh milk and other pasteurised beverages), the temperature can compromise tag readability. RFID systems efficiency may also be affected by tag-to-reader antenna misalignment, which often occurs for cylindrical section containers. Experimentation has been conducted to evaluate the effect of temperature, different solute type and tag orientation on the readability of a commercial passive RFID UHF tag (Lab Id UH100) applied to a HDPE (Highdensity polyethylene) bottle. To compare readability, the minimum transmitted power output that allows the tag-backscattered signal (Pmin) to be acquired by the reader was measured in standard controlled conditions. It was observed that solution temperature strongly affected the readability of passive UHF RFID labels. The correlation between temperature and readability was observed being positive or negative depending on the adopted solute type. In particular, an improvement in readability was detected for deionized water, sucrose and ethanol solutions when temperature was increased from 4°C to 25°C. Readability decreased for citric acid and NaCl solutions in the same temperature range. Reading performance was highly influenced by bottle rotation along the vertical axis, which caused both the misalignment of the tag-to-reader mutual orientation and the radio wave reflection and absorption phenomena due to the presence of the considered solutions in different positions.

Performance Optimization of Neural-network Based Colour Measurement Tools for Food Applications

Performance Optimization of Neural-Network Based Colour Measurement Tools for Food Applications Paolo Barge, Lorenzo Comba, Paolo Gay, Davide Ricauda Aimonino, Cristina Tortia*, Nahid Aghilinategh, Mohammad Jafar Dalvand DI.S.A.F.A. – Università degli Studi di Torino, 2 Largo Paolo Braccini, 10095 Grugliasco (TO), Italy DENERG – Politecnico di Torino, 24 Corso Duca degli Abruzzi, 10129 Torino, Italy D.A.M.E. University of Tehran, Karaj, Iran cristina.tortia@unito.it