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The fruit industry needs rapid and non-destructive techniques to evaluate the quality of the products in the field and during the post-harvest phase. The soluble solids content (SSC), in terms of °Brix, and the flesh firmness (FF) are typical parameters used to measure fruit quality and maturity state. Hyperspectral imaging (HSI) is a powerful technique that combines image analysis and infrared spectroscopy. This study aimed to evaluate the potential of the application of the Vis/NIR push-broom hyperspectral imaging (400 to 1000 nm) to predict the firmness and the °Brix in apricots (180 samples) during storage (11 days). Partial least squares (PLS) and artificial neural networks (ANN) were used to develop predictive models. For the PLS, R2 values (test set) up to 0.85 (RMSEP=1.64 N) and 0.72 (RMSEP=0.51 °Brix) were obtained for the FF and SSC, respectively. Concerning the ANN, the best results in the test set were achieved for the FF (R2=0.85, RMSEP=1.50 N). The study showed the potential of the HSI technique as a non-destructive tool for measuring apricot quality even along the whole supply chain.

INTRODUZIONE Come ben noto, il contenuto in etil esteri degli acidi grassi (EEAGs) è considerato un parametro diretto di qualità da applicarsi per definire l’appartenenza di oli vergini di oliva (VOOs) ad una specifica categoria (limite fissato a ≤35 mg/kg per la categoria extra vergine di oliva per la legislazione UE) ed è anche ritenuto un parametro indiretto utile per mettere in luce possibili miscele fraudolente tra un olio extra vergine di oliva ed un olio soft deodorato [1]. In questo lavoro è stato proposto un approccio analitico alternativo al metodo ufficiale con lo scopo di offrire una procedura non in linea HPLC-GC-FID migliora tiva in termini di tempo di analisi, volume di solventi e livello di complessità. Più nello specifico, è stato impiegato l’HPLC per collezionare i EEAGs dagli oli vergini di oliva (VOOs) al posto della tradizionale cromatografia liquida su colonna. Inoltre, è stato testato anche un iniettore di vaporizzazione a temperatura programmata (PTV) come possibile alternativa a quello on-column poichè il PTV è considerato più versatile consentendo il controllo programmato e l’ottimizzazione della modalità di iniezione (split/splitless). Le prestazioni del metodo alternativo sono state valutate controllando i risultati ottenuti per differenti parametri che caratterizzano il protocollo di validazione interna [2]. A tale scopo, sono state analizzate tipologie specifiche di campioni quali olio di oliva raffinato aggiunto di cinque concentrazioni diverse di standard puri degli analiti di interesse e campioni reali VOOs caratterizzati da concentrazioni diverse di EEAGs (basso, medio ed alto contenuto di EEAGs) ed applicando in parallelo i due metodi (alternativo vs ufficiale). INTRODUCTION As well known, the content in fatty acid ethyl esters (FAEEs) represents a direct quality parameter to define the quality grade of virgin olive oil (VOOs) (limit set at ≤35 mg/kg oil for extra virgin olive oil category for EU regulation), and it is also considered an indirect parameter to detect fraudulent mixtures of EVOO with lower quality oils such as soft deodorized olive oils [1]. In this work, the official method has been revised to propose an alternative off-line procedure based on HPLC-GC-FID, more suitable in terms of time of analysis, volume of solvents and level of complexity. Specifically, the analytical protocol proposed HPLC for collecting FAEEs from VOOs instead of the traditional liquid chromatography of the official method. Moreover, a programmed temperature vaporizer (PTV) injector was tested as an alternative to the on-column one because PTV is considered a more versatile option as the temperature control is time-programmed and the injection mode (split/splitless) can be optimized. The performance of the alternative method was evaluated, checking the results in terms of several parameters regarding in-house validation protocol [2]. For this control, specific kinds of samples as refined olive oil spiked with five concentrations of a pure standard of analytes of interest and real VOOs characterized by different contents of FAEEs (low, medium, high) were analyzed applying in parallel the two methods (alternative vs official) (see the Figure). RESULTS The main advantages of this revised protocol may be summarized as: i) significant reduction in time and solvents needed (reduction of more than 50% and 80% for time and solvents, respectively compared to the official procedure); ii) simplification of the separation step of FAEEs fraction avoiding the manual packing of the glass column for the liquid chromatography; iii) satisfactory performance in terms of in-house validation results: linearity showed linear response between 2.5 and 50 mg/L; percentages of standard deviation related to intra-day and inter-day precision were lower than 15%; LOD and LOQ were lower than 1 and 1.5 mg/kg, respectively; in the case of the concentration of FAEEs closer to the legal limit, the recoveries of each analyte were higher than 94%; iv) no significant differences were evidenced for analytes of interest when the alternative procedure offline HPLC-GC-FID with PTV injector was applied to actual samples with low, medium and high content of FAEEs with respect to the official method.

Capacitance and Time Domain Reflectometry (TDR) measurements were conducted to assess the basic qualitative and compositional parameters of extra virgin olive oils (EVOOs). Capacitance values obtained by a parallel plates capacitor in the frequency range of 1-9 kHz were used to build predictive models of the water content from 16 different commercial EVOOs by Partial Least Square (PLS) analysis. TDR signals were processed by Principal Component Analysis (PCA) to discriminate between EVOO samples produced with two olive cultivars (“Correggiolo” and “Canino”) both characterized by different contents of fatty acids alkyl esters due to the different storage times of the olives. From PLS regression, R2 values of 0.921 (RMSE=100 mg/kg oil) and 0.909 (RMSE=106 mg/kg oil) were observed for the prediction of the water content in cross and test set validations, respectively. PCA appeared to show differences between samples in terms of sum of fatty acid methyl esters and fatty acids ethyl esters within the same cultivar of olives. These first results are promising for the assessment of the EVOO parameters. However further studies should be conducted in order to better understand the relationship between the dielectric behavior and the EVOO composition.

Monitoring the quality attributes of grapes is a practice that allows the state of ripeness to be checked and the optimal harvest time to be identified. A non-destructive method based on hyperspectral imaging (HSI) technology was developed. Analyses were carried out directly in the field on a ‘Sangiovese’ (Vitis vinifera L.) vineyard destined for wine production, by using a Vis/NIR (400–1000 nm) hyperspectral camera. One vineyard row was analysed on 13 different days during the pre-harvest and harvest time. The soluble solids content (SSC) expressed in terms of °Brix was measured by a portable digital refractometer. Afterwards, the grape samples were split in two classes: the first one composed by the samples characterised by a °Brix lower than 20 (not-ripe), while the second one by the samples with a °Brix higher than 20 (ripe). Grape mean spectra were extracted from each hyperspectral image and used to predict the SSC by partial least squares regression (PLS), and to classify the samples into the two classes by PLS discriminant analysis (PLS-DA). SSC was predicted with a R2 = 0.77 (RMSECV = 0.79 °Brix), and the samples were correctly classified with a percentage from 86 to 91%. Even if the number of wavelengths was limited, the percentages of correctly classified samples were again within the above-mentioned range. The present study shows the potential of the use of HSI technology directly in the field by proximal measurements under natural light conditions for the prediction of the harvest time of the ‘Sangiovese’ red grape.

The measurement of vegetation indexes that characterise the plants growth, assessing the fruit ripeness or detecting the presence of defects and diseases, is a key factor to gain high quality of fruit or vegetables. Such evaluation can be carried out using both destructive and non destructive techniques. Among non-destructive techniques, hyperspectral imaging (HSI), combining image analysis and visible/near-infrared spectroscopy, looks particularly useful. Many studies have been published concerning the use of hyperspectral cameras in the agronomic and food field, especially in controlled laboratory conditions. Conversely, few studies described the application of HSI technology directly in field, especially involving ground-based systems. Results suggest that this technique could be particularly useful, even if the role of environmental variables has to be considered (e.g., intensity and incidence of solar radiation, wind or the soil in the background). In this paper, recent in-field HSI applications based on ground systems are reviewed.

The quality assessment, in terms of lipid oxidative status, of food products stored in the long-term is of great importance, especially those with a high lipid content. Specifically, companies working in this sector need feasible, simple, and fast techniques that are suitable for quality or process control. Herein, a fingerprinting approach, based on headspace analysis carried out by flash gas chromatography electronic nose (FGC E-nose) and multivariate data analysis was applied to pistachio and gianduja spreads. These samples, differently packaged, were stored in climatic chambers at 40 °C for 180 days and their headspace fraction was analyzed periodically for a total of 15 sampling times. Principal component analysis showed a clear separation according to the packaging type for both pistachio and gianduja samples. Partial least squares regression models were developed to predict the storage time considering the aggregated data (R2 up to 0.985, RMSEP = 6.16 days) or separately (R2 up to 0.989, RMSEP = 5.71 days). Based on the obtained residual prediction deviation (RPD from 4.4 to 8.5 in prediction), the models can be considered suitable for use in quality control in an industrial environment.

Wafer cookies combine two or more layers of wafer sheets with intermediate layers of cream filling and later coating with chocolate. During storage, wafer cookie quality, especially in terms of mechanical properties, is mainly affected by moisture migration from the cream or chocolate and moisture absorption from air. This study aimed to assess the storage of wafer cookies by destructive (water activity, mechanical properties, and sensory acceptance) and non-destructive methods (image analysis, NIR spectroscopy and hyperspectral imaging HSI). Furthermore, two packaging types were considered. Samples were stored at 18 °C (RH = 50%) and analysed after 2, 4, 5, 6, 7 and 8 months. Good linear relations (R2 up to 0.84) were found between water activity and mechanical parameters, confirming the dependence between textural aspects and water content. By adding a multi-material packaging layer, the shelf life significantly increased in terms of sensory acceptance (crispness). No significant differences were found between the surface colour parameter (white index) attributable to fat bloom formation. PCA results of NIR and HSI spectra showed a clear separation between samples acquired at time 0 and those analysed during storage that was related with the packaging type and storage time. PLS models developed to estimate the storage time showed R2 ranging from 0.926 (RMSECV = 0.63 months) to 0.960 (RMSECV = 0.52 months), while the water activity ranged from 0.858 to 0.928 (RMSECV = 0.02 months). The PLS models based on HSI spectra were used to obtain predictive images of water activity or storage time

Moisture migration plays an important role in the stability and quality of bakery products. In this study, pectin, alginate and whey protein edible coating was used as an edible barrier to evaluate its effectiveness for retaining the quality of bread by reducing moisture loss and textural changes during storage. Mini-buns as model systems were applied with 1 layer and 2 layers of coating and evaluated for moisture and texture attributes by both mechanical and spectroscopic techniques. The coatings displayed a retaining effect with the percentage increase in crumb hardness lower for coated samples (1 L: 126.5% and 2 L: 231.2%) than control samples (Control: 271.8%). Further, the spectral data for the crust and crumb surfaces were pre-treated and subjected to Principal Component analysis (PCA) for the evolution along storage time. In particular for moisture content, discrimination at 8 h for crust and after 24 h for crumb was noted for both 1 L and 2 L coating layers with a R2 > 0.85. Subsequently, PLS models with spectral data described satisfactorily the evolution of hardness with low (

The application of edible coating in bakery products could be a suitable alternative to maintain safety, textural and organoleptic characteristics during the storage. To achieve a continuous coating layer, the coating solvent should be eliminated by a drying process, avoiding the food internal dehydration. The main factors that influence the drying time of the coating are the temperature, thickness of the coating and the solvent concentration. In order to define the optimal drying time, numerical modelling could provide a suitable alternative to experimental techniques. In this study, finite elements models able to describe the heat and moisture transfer inside and on the surface of coated bun breads, as function of drying temperature, time and coating thickness were developed and validated. A good agreement was obtained between calculated and experimental data reporting RMSE of 0.05 and 0.04 kg water kg solid−1 for the samples dried at 25 and 60 °C, respectively. A relation between the optimal drying time, coating thickness and the drying temperature was determined (R 2 = 0.981, 95% confidence bounds). The model could be used for other coating formulations and bakery products, simply by changing material properties and geometrical dimensions.

Non-thermal atmospheric plasma (NTAP) has gained attention as a decontamination and shelf-life extension technology. In this study its effect on psychrotrophic histamine-producing bacteria (HPB) and histamine formation in fish stored at 0–5°C was evaluated. Mackerel filets were artificially inoculated with Morganella psychrotolerans and Photobacterium phosphoreum and exposed to NTAP to evaluate its effect on their viability and the histidine decarboxylase (HDC) activity in broth cultures and the accumulation of histamine in fish samples, stored on melting ice or at fridge temperature (5°C). NTAP treatment was made under wet conditions for 30 min, using a dielectric barrier discharge (DBD) reactor. The voltage output was characterized by a peak-to-peak value of 13.8 kV (fundamental frequency around 12.7 KHz). This treatment resulted in a significant reduction of the number of M. psychrotolerans and P. phosphoreum (≈3 log cfu/cm2) on skin samples that have been prewashed with surfactant (SDS) or SDS and lactic acid. A marked reduction of their histamine-producing potential was also observed in HDC broth incubated at either 20 or 5°C. Lower accumulation of histamine was observed in NTAP-treated mackerel filets that have been inoculated with M. psychrotolerans or P. phosphoreum and pre-washed with either normal saline or SDS solution (0.05% w/v) and stored at 5°C for 10 days. Mean histamine level in treated and control groups for the samples inoculated with either M. psychrotolerans or P. phosphoreum (≈5 log cfu/g) varied from 7 to 32 and from 49 to 66 μg/g, respectively. No synergistic effect of SDS was observed in the challenge test on meat samples. Any detectable amount of histamine was produced in the meat samples held at melting ice temperature (0–2°C) for 7 days. The effects of NTAP on the quality properties of mackerel’s filets were negligible, whereas its effect on the psychrotrophic HPB might be useful when time and environmental conditions are challenging for the cool-keeping capacity throughout the transport/storage period.

Sorption behavior and glass transition of frozen parsley were investigated in order to study the physical modifications, represented as state diagram to figure out information about product behavior for storage and supply chain handling. Frozen products may be located in the state diagram in all the possible freezing temperatures to understand the structure state and study feasible corrective actions mainly focused on temperature and solid content. Parsley was totally dehydrated and equilibrated at selected relative humidity. Sorption behavior was evaluated by saturated salt slurry method and sorption isotherm fitting, while solid components in terms of mass fraction were investigated by using differential scanning calorimetry. Brunauer–Emmet–Teller (BET) model well fitted with moisture and water activity data (R2 = 0.995, p-level < 0.05). The characteristic ranges of stability, in terms of system mobility and physical modification, are the monolayer values (0.240 water activity; 0.052 kg/kg dry basis) and the critical water activity range (0.424 water activity; 0.078 kg/kg dry basis). Glass transition and melting temperature were used to define parsley state diagram. Different zones figure out a specific physical behavior: depending on solid content and temperature. Unfrozen water was estimated as monolayer BET value 0.84 kg/kg wet basis and extrapolated from state diagram 0.984 kg/kg wet basis. Practical applications: Frozen high-quality product and energy efficiency can be obtained by a correct temperature management. Thermophysical properties of parsley represented in a state diagram are reported in the typical solute and temperature range of freezing process and storage. These data can relate physical structure and temperature, allowing different possible conditions management.

Biochemical reactions and microbiological activity are responsible of fresh fish short shelf life. The deterioration processes involve a series of changes in the product quality affecting its appearance, odor and taste. The present work aims at discriminating samples of sardines during the shelf life at 4°C by means of a Vis/Nir HyperSpectral Camera (HSC) camera. After preprocessing techniques, Principal Component Analysis (PCA) was used to evidence spectral differences related to the deterioration processes. By analyzing the score plot of the first two principal components (PC1 = 94.1%; PC2 = 3.0 %), a distribution according to time was observed, showing that hyperspectral data could be a good indicator of fish freshness and decay state progress.

The moisture diffusivity of food is a very important physical parameter to model baking processes. Unfortunately, specific moisture diffusivity values are not easily found in literature, especially measured or calculated during the baking processes. The main methods used to estimate the moisture diffusivity are based on the second Fick's law, but there are significant differences in the way of applying these laws. The aim of this work is to estimate the effective moisture diffusivity in baking of a small flat cake by using the inversion of a numerical model based on the coupling of heat and mass transfer. The temperature and moisture dependency of the diffusivity is evaluated. Results are compared with those obtained by using a fitting method. The inverse method allows to estimate the effective moisture diffusivity close to those reported in literature for similar bakery products (constant values). The impact of the moisture concentration appears to be very restricted and it tends to decrease with increasing the oven temperature. Subsequently, the obtained effective diffusivity was implemented on a direct Finite Element (FE) model simulating a whole cake for different baking temperatures. The direct model validation (mean moisture content and temperature) shows determination coefficients ranging from 0.921 to 0.996 confirming the robustness of the diffusivity parameters obtained by the inverse method.

Walk behind tractors have some advantages over other agricultural machines, such as the cheapness and the easy to use, however the driver is exposed to high level of vibrations transmitted from handles to hand-arm system and to shoulders. The vibrations induce discomfort and early fatigue to the operator. In order to control the vibration transmissibility, a ballast mass may be added to the handles. Even if the determination of the appropriate ballast mass is a critical point in the handle design. The aim of this research was to study the influence of the handle mass modification, on the dynamic structure behaviour. Modal frequencies and subsequent transmissibility calculated by using an analytical approach and a finite elements model, were compared. A good agreement between the results obtained by the two methods was found (average percentage difference calculated on natural frequencies equal to 5.8±3.8%). Power tillers are made generally by small or medium-small size manufacturers that have difficulties in dealing with finite element codes or modal analysis techniques. As a consequence, the proposed analytical method could be used to find the optimal ballast mass in a simple and economic way, without experimental tests or complex finite element codes. A specific and very simple software or spreadsheet, developed on the base of the analytical method here discussed, could effectively to help the manufacturers in the handlebar design phase. The choice of the correct elastic mount, the dimensioning of the guide members and the ballast mass could be considerably simplified.

Solid and liquid components coexist into glassy and amorphous structures of food complex matrixes. Both states admit movements, promoting physical modifications to a more thermodynamically stable system. Green and roasted coffee beans are principally characterized by a glassy structure that slowly evolves during storage. The aim of this study was to assess calorimetric and dielectric properties in combination, as a useful multi-analytical technique to improve the understanding of the motion mechanism of localized molecules. After equilibration at different water activities (aw) for the determination of sorption isotherms of green and roasted coffee, the glass transition temperature (Tg) of the samples has been measured by using differential scanning calorimetry (DSC). Increasing the aw from 0.155 to 0.512, the Tg shifted from 48.76 (±0.04) to 34.89 (±0.02) °C for green coffee and from 45.73 (±0.05) to 40.15 (±0.10) °C for the roasted one. The spectroscopic fingerprint of the matrix has been determined by dielectric measurements in terms of “gain” spectra (related to the imaginary part of permittivity). The maximum values of the determination coefficient (R2), obtained by linear correlation between spectral data and water activity or glass transition values for a specific frequency of the whole range (1.6 GHz–2.7 GHz), were 0.999 and 0.943 for green, and 0.997 R2 and 0.925 R2 for roasted coffee respectively.

Drying is one of the most important fruit and vegetable preservation method useful to remove water from fresh materials. This permits to avoid growth of bacteria, yeasts or moulds. To better understand the heat and mass transfer process that take place during drying, numerical models can be used. The effective diffusivity determination is a crucial aspect for the development of drying models. The diffusivity is affected by the product temperature and moisture content. The aim of this study was to develop a method, based on the inversion of a finite element model, to estimate the moisture diffusivity of fruits during drying as a simultaneous function of temperature and moisture content. The research work was divided in three phases: i) experimental determination of the moisture concentration versus time in various fruits during the drying process; ii) development of a numerical heat and mass transfer model for the determination of moisture content versus time; iii) parameter estimation of moisture diffusivity as a function of temperature and moisture content, by minimizing the distance between numerical model and experimental results using a feasible optimization algorithm. The estimated moisture diffusivity coefficients are close to those reported in literature for the same fruits (banana and apple), but obtained by others approaches. The experimental and calculated moisture contents are in good agreement showing a determination coefficient R2>0.97.

On or off-line controls of the freezing process, used to ensure the desired final quality of frozen dairy desserts, is an important task, especially for manufacturers who consider the standard of production as a primary goal. One of the products of interest in this context is the milkshake, a drink that contains ice crystals and a precise content of air. Herein, we used three different techniques, based on as many prototypes, to monitor and control the freezing process of a milkshake based product over a period of 1–29 h: an optical technique based on a digital microscope and image analysis, a rotational rheometer and a capacitive device. The optical technique characterized crystal growth and air content during freezing, and can be regarded as a reference method. The dimension of ice crystals and content of air bubbles showed a non-linear increase during preparation time. Correlations were high, with coefficients of determination up to 0.991. Parameters measured by other techniques, such as a rotational rheometer and a capacitive device, also showed good, logarithmic correlations with freezing time, with R 2 values up to 0.964. Correlations between the main freezing parameters and data obtained with the rotational and capacitive techniques appeared good ( R 2 up to 0.983). Thus, these latter techniques might conceivably replace more complicated and expensive optical methods used to monitor the freezing process, especially when processing a product characterized by a constant composition.

In the sausage industry, ripening is considered to be the most important phase of the production process. Numerical models were successfully used to study the mass transport in many food during baking, freezing, ripening and drying process. The aim of this research was to develop two finite element models of water diffusion inside a salami, taking account of the vapour exchange phenomena at the surface. One model was based on the real fat and meat distribution, as acquired by image analysis, while a second one, more simple, considering the salami material as homogeneous and imposing an equivalent value of diffusion coefficient, based on compositional equations (parallel, series, Maxwell and Krisher) or literature data. The vapour exchange phenomenon at the surface was described using a surface mass transfer coefficient (hm) calculated on the basis of the well-known Chilton–Colburn analogy. The two models were compared and validated with experimental mean moisture concentration. The agreement between mean simulated and experimental values was reported in terms of determination coefficients (R2). For all models, the R2 value is higher than 0.95, supporting that the experimental and all calculated data are in good agreement. The less good data were obtained with the simplest model, based on equivalent diffusion coefficient coming from literature (R2 = 0.955, RMSE = 1665 mol/m3). Very small difference was observed between results related to structural models. The finite element model based on the real fat and meat distribution underestimated experimental results, giving results not far from structural models, but giving the best result at the end of ripening time. The deviation from experimental results probably is due to geometrical reconstruction uncertainties and particularly on binarisation triggering on a grey scale. Considering the real fat distribution, a more complex model, but not more precise results than those calculated considering an equivalent homogeneous material, were observed.

The aim of this work was to study the possibility to improve the shelf life of a traditional Italian flat bread named Piadina, typically cooked in the Romagna region, by using sourdough fermentation and enzymes. To evaluate Piadina quality during storage, chemical parameters, subjective and objective mechanical tests were used. Moreover, NIR spectroscopy, coupled with principal component analysis (PCA) and partial least square regression (PLS), was used to discriminate the samples as a function of formulation and to predict storage time, respectively. The results show that the samples containing yeasts and lactic acid bacteria have higher values in water content. This result is also confirmed by the fact that the average water activity of the control sample is significantly lower compared with that of the samples containing enzymes, yeasts, lactic acid bacteria. For all formulations, rollability is significantly affected by storage time with decreased scores observed during storage. The synergistic action between enzymes, yeasts and lactic acid bacteria increases the shelf life, in terms of rollability. The evaluated texture parameters did not significantly correlate with subjective rollability. The PCA applied to spectroscopic data shows a clear separation between samples with different sourdough percentage, while the results of PLS regression, conducted to estimate the storage time, report determination coefficient spanning from 0.959 to 0.969.

Thermal conductivity of a food material is an essential physical property in mathematical modelling and computer simulation of thermal processing. Effective thermal conductivity of non-homogeneous materials, such as food matrices, can be determined experimentally or mathematically. The aim of the following research was to compare the thermal conductivity of short pastry biscuits, at different baking stages (60-160 min), measured by a line heat source thermal conductivity probe and estimated through the use of thermo-physical models. The measures were carried out on whole biscuits and on powdered biscuits compressed into cylindrical cases. Thermal conductivity of the compacted material, at different baking times (and, consequently at different moisture content), was then used to feed parallel, series, Krischer and Maxwell-Eucken models. The results showed that the application of the hot wire method for the determination of thermal conductivity is not fully feasible if applied directly to whole materials due to mechanical changes applied to the structure and the high presence of fats. The method works best if applied to the biscuit component phases separately. The best model is the Krischer one for its adaptability. In this case the value of biscuit thermal conductivity, for high baking time, varies from 0.15 to 0.19 Wm–1 K–1, while the minimum, for low baking time, varies from 0.11 to 0.12 Wm–1 K–1. These values are close to that reported in literature for similar products.

Knowledge of moisture diffusivity coefficients of water in food is a very important physical parameter for design, modelling and simulation of different food plants and related processes such as baking, drying and ripening. Unfortunately specific moisture diffusivity values are not easily found in literature, particularly for processed foods. The aim of this study was to develop a method, based on the inversion of finite element models, to estimate the moisture diffusivity in different solid food products. An example on salami, biscuit and flat bread is shown. The research work was divided in three phases: experimental determination of the moisture concentration versus time in various food products stored in water saturated atmosphere; development of a numerical model of water transfer inside the food product for the numerical determination of moisture content versus time and parameter estimation of moisture diffusivity, by minimizing the distance between numerical model and experimental results using the Levenberg–Marquardt algorithm. The estimated moisture diffusivity coefficients resemble those reported in literature for almost similar products (3.857E − 12, 6.804E − 11 and 1.792E − 12 m2/s for salami, biscuits and flat bread respectively). The obtained values were then used for solving direct models, in unsteady conditions, showing a good agreement with experimental data. The method may be used on different food materials and it is possible to hypothesize an integrated automatic instrument, useful both for laboratory and industrial purposes.

The mechanical vibrations characterized by a frequency lower than 200 Hz could promote the cells breakage and improve the oil extraction process by avoiding, at the same time, the negative effects on the commercial qualitative parameters due to the use of the heating during malaxation. Vibration tests were conducted by means of an electrodynamic shaker in order to find the optimal frequency levels of excitation, able to put in a resonant condition the olive paste. Sinusoidal accelerations at constant acceleration (120 m/s2), in a range between 5 and 200 Hz were explored. The 50 Hz and 80 Hz frequencies were able to put in resonant condition the olive paste. In the vibrated samples at 50 Hz (15 min of treatment), the maximum increment of the extraction efficiency (about 53% in comparison with the control), was observed. Further studies could be conducted in order to assess the synergic effect of the mechanical vibrations and the malaxation on the oil extraction efficiency, with the aim of reducing the time of the whole phase and avoiding changes in the oil quality traits.

Herein, the potential of Fourier transform infrared spectroscopy (FTIR) spectroscopy coupled with principal component analysis and artificial neural networks to discriminate butters obtained from milk creams collected in different seasons (spring, summer or winter) and produced from two feeding regimens (traditional or unifeed) in the Parmigiano Reggiano cheese area was investigated. The predictive ability of neural networks to predict the season of production was 100%. The favorable results obtained by artificial neural network (ANN) analysis were in agreement with those reported by principal component analysis (PCA) analysis. The ability of ANNs to predict the feeding regimens was 90.0%, 75.0% and 75.0%, respectively, for samples collected in spring, summer and winter. These results also confirm that the method is highly suitable for its intended purpose. Highlights ► 405 FT-IR spectra of butter were analyzed by PCA and ANN. ► ANN discriminate the season of production and dietary regimen of butters. ► The ability of ANN to predict the season of production of milk cream was 100%.

The seasonal variation of the fatty acids composition of butters were investigated over three seasons during a 12-month study in the protected designation of origin Parmigiano-Reggiano cheese area. Fatty acids were analyzed by GC-FID, and then computed by artificial neural networks (ANN). Compared with spring and winter, butter manufactured from summer milk creams showed an optimal saturated/un-saturated fatty acids ratio (−8.89 and −5.79%), lower levels of saturated fatty acids (−2.63 and −1.68%) and higher levels of mono-unsaturated (+5.50 and +3.45%), poly-unsaturated fatty acids (+0.65 and +0.17%), and rumenic acid (+0.55 and +3.41%), while vaccenic acid had lower levels in spring and higher in winter (−2.94 and +2.91%). Moreover, the ANN models were able to predict the season of production of milk creams, and classify butters obtained from spring and summer milk creams on the basis of the type of feeding regimens. Practical applications: The investigation on variables that affect the milk fatty acids composition can improve the quality of milk across all systems, and the combination of chromatographic and computational techniques will ensure a secure traceability enabling producers to characterize dairy products.

The nondestructive assessment of apricot fruit quality (Bora cultivar) was carried out by means of FT-NIR reflectance spectroscopy in the wavenumber range 12000 to 4000 cm−1. Samples were harvested at four different ripening stages and scanned by a fiber optical probe immediately after harvesting and after a storage of 3 d (2 d at 4 °C and 1 d at 18 °C); the flesh firmness (FF), the soluble solids content (SSC), the acidity (A), and the titratable acidity (malic and citric acids) were then measured by destructive methods. Soft independent modeling of class analogy (SIMCA) analysis was used to classify spectra according to the ripening stage and the storage: partial least squares regression (PLS) models to predict FF, SSC, A, and the titratable acidity were also set-up for both just harvested and stored apricots. Spectral pretreatments and wavenumber selections were conducted on the basis of explorative principal component analysis (PCA). Apricot spectra were correctly classified in the right class with a mean classification rate of 87% (range: 80% to 100%). Test set validations of PLS models showed R2 values up to 0.620, 0.863, 0.842, and 0.369 for FF, SSC, A, and the titratable acidity, respectively. The best models were obtained for the SSC and A and are suitable for rough screening; a lower power prediction emerged for the other maturity indices and the relative predictive models are not recommended. Practical Application: The results of the study could be used as a tool for the assessment of the ripening stage during the harvest and the quality during the postharvest storage of apricot fruits.

A hot air assay was set up for the surface decontamination of table eggs experimentally contaminated by Salmonella enterica serovar Enteritidis. A hot air apparatus was built and a treatment of two shots of 8 s at 600 °C with an interval of 30 s of cold air was chosen and applied on contaminated eggs. The S. Enteritidis load on eggshells as well as the quality traits of the egg components of 190 treated and 190 not treated eggs was investigated during 24 days of storage at 20 °C. Hot air treatment reduced the S. Enteritidis load on eggshells of up to 1.9 log. No significant changes to any of the quality traits tested were recorded. These results suggest the usefulness of hot air pasteurisation for the surface decontamination of table eggs.

The increase in size of the air cell is related to the aging process of the eggs. According to the European Commission Regulation, eggs must be classified in A (air cell size higher than 4 mm), and A “extra” (air cell size lower than 4 mm) categories by candling inspection. This technique is unable to non-destructively assess the size of the air cell during egg grading. The present research studies the possibility to nondestructively grading shell eggs from dielectric parameters obtained by means of a sine wave RF oscillator, a parallel inductance and capacitance circuit. In particular, dielectric parameters and egg dimensional characteristics were used to set up multi-layer (MLP) artificial neural networks. Using MLP with two hidden layers, eggs can be correctly graded in A and A “extra” categories (test validation) within a mean performance close to 90%.

Water mobility and availability in coffee play an important role in the roasting and storage process, depending on the interactions between the aqueous phase and the biopolymeric matrix. The aim of this research was to deepen the understanding of these aspects in green and roasted coffee, by means of the joint application of traditional saturated salt slurry (DES) and innovative dynamic dewpoint (DDI) methods for adsorption isotherm generation. In addition, on green and roasted samples at different hydration levels, the assessment of proton transverse relaxation time by TD-NMR and dielectric properties through waveguide spectroscopy in the spectral ranges 2–3, 5–6 GHz and 17–18 GHz have been performed. Green coffee exhibited above the critical a w a different behavior if observed by means of DES or DDI, demonstrating that its hydration is strictly time dependent because of its heterogeneous structure; this phenomenon was not detectable for roasted coffee, that showed very similar results with the two different techniques. The measurement of T 2 by using TD-NMR permitted to study the mobility of different proton pools with a high level of details, allowing the quantitative assessment of exchange/interaction phenomena occurring along matrix re-hydration and the consequent increase of water proton mobility. At low frequencies, the described dielectric technique showed high potentiality for the non-destructive estimation of water content of green and roasted coffee. At higher frequencies, the obtained signal seems to be more related to water/solid matrix interactions and water activity.

The non-destructive assessment and control on and off-line of some quality parameters of the grated cheese is a goal of the dairy industries and distributors. The present research is addressed to explore the possibility of estimating the percentage of moisture, proteins, added rind, and the ripening time of this kind of cheese by a capacitive technique supported by basic statistical analysis and artificial neural networks (ANN). An instrumental chain composed by a parallel plate capacitor probe, for housing the cheese in a suitable container, and a LCR meter, were used to measure the capacitance of different product mixtures, in the frequency range from 100 Hz to 10 kHz. Samples were prepared by mixing cheeses ripened from 8 months to 36 months and rind percentage from 0% to 50%. The results show that moisture and protein percentages can be estimated in a quite good manner with a linear correlation ( R 2 up to 0.81) and ANN ( R 2 up to 0.83). The ripening time is well linearly assessed in the cheese without the addition of rind ( R 2 = 0.994) or if the rind percentage is known ( R 2 from 0.872 to 0.963). The rind percentage is very well linearly estimated if the ripening time is known ( R 2 from 0.914 to 0.987). Estimation of the rind percentage if the ripening time is unknown appears more difficult (max R 2 = 0.658) because both ripening and addition of rind involve a decrease in capacitance. The frequency at which the capacitance is measured shows only a weak influence in the goodness of the parameters determination. On the whole and as a trend, the correlations improve increasing the frequency. The obtained results, the conformation of the probe and the minimal data treatments mean that this technique can be considered to be applied in the chains of the grated cheese packaging.

Ripening, in the sausages manufacturing process, has an influence over the main chemical, microbiological and physical transformations that take place inside these products and that define the final organoleptic properties. A number of studies indicate that the final quality and safety standards achieved by the sausage manufacturing process can be considered to be strictly dependent from the specific ripening conditions. Among the main phenomena that occur during ripening, those involving the water transfer by diffusion are crucial. As a consequence the aim of this research was to develop a parametric numerical model able to describe water diffusion phenomena occurring inside the salami and the vapour exchange phenomena that take place at the interface between the product surface and the environment. Mass transfer equations inside the sausage volume were numerically solved using a finite element technique. The sausage material was described by two different ways and models: the first one considering a global diffusion coefficient experimentally measured and the second considering the estimated diffusion coefficient calculated on the base of meat and fat properties. In the last case, to describe the real distribution of the fat in the sausage and define the model geometry, a 2D image of a sausage slice was used. The results of two models were compared and experimentally validated. The numerical and experimental data were find to be in good agreement. Slight differences between the data obtained with the two models were observed.

Parmigiano–Reggiano (PR) cheese is one of the oldest traditional cheeses produced in Europe, and it is still one of the most valuable Protected Designation of Origin (PDO) cheeses of Italy. The denomination of origin is extended to the grated cheese when manufactured exclusively from whole Parmigiano-Reggiano cheese wheels that respond to the production standard. The grated cheese must be matured for a period of at least 12 months and characterized by a rind content not over 18%. In this investigation the potential of near infrared spectroscopy (NIR), coupled to different statistical methods, were used to estimate the authenticity of grated Parmigiano Reggiano cheese PDO. Cheese samples were classified as: compliance PR, competitors, non-compliance PR (defected PR), and PR with rind content greater then 18%. NIR spectra were obtained using a spectrophotometer Vector 22/N (Bruker Optics, Milan, Italy) in the diffuse reflectance mode. Instrument was equipped with a rotating integrating sphere. Principal Component Analysis (PCA) was conducted for an explorative spectra analysis, while the Artificial Neural Networks (ANN) were used to classify spectra, according to different cheese categories. Subsequently the rind percentage and month of ripening were estimated by a Partial Least Squares regression (PLS). Score plots of the PCA show a clear separation between compliance PR samples and the rest of the sample was observed. Competitors samples and the defected PR samples were grouped together. The classification performance for all sample classes, obtained by ANN analysis, was higher of 90%, in test set validation. Rind content and month of ripening were predicted by PLS a with a determination coefficient greater then 0.95 (test set). These results showed that the method can be suitable for a fast screening of grated cheese authenticity.

In questo lavoro vengono discussi i risultati di una ricerca decennale sulla “qualità in tazza” del caffè espresso, condotta presso 688 esercizi di vendita di 6 aree geografiche del centro-nord Italia. Nella ricerca sono state prese in considerazione variabili di processo quali: impianto di torrefazione, macinadosatore, macchina di estrazione, miscela, pressione e temperatura dell’acqua, peso del macinato e grado di pressione all’interno del filtro. Per la “qualità in tazza” sono stati valutati: consistenza e altezza della crema, pH, gradi Brix e volume dell’estratto. Oltre 9.000 dati sono stati elaborati mediante l’Anova, il Mann-Whitney test e il Levene test. L’Analisi delle Componenti Principali (PCA) è stata applicata ai dati relativi ai campioni raccolti in aree diverse e per discriminare gli anni di indagine. Tipo di macchina di estrazione, tipo di macinadosatore e formazione dell’operatore sono risultati gli elementi più significativi che influenzano la qualità del caffè espresso.

Ripening, in the dry sausages manufacturing process, has an influence over the main physical, chemical and microbiological transformations that take place inside these products and that define the final organoleptic properties of dry sausages. A number of study about the influence of ripening conditions on the main chemical and microbiological characteristics of dry sausages is available today. All these studies indicate that the final quality and safety standards achieved by the sausage manufacturing process can be considered to be strictly dependent from the specific ripening conditions. The water diffusion inside a seasoned sausage is surely an aspect of primary importance with regard to the quality of final product. As a consequence the aim of this research was to develop two parametric numerical models, concerning the moisture diffusion physics, describing salami ripening and storage. Mass transfer equations inside the sausage volume were numerically solved using a finite element technique. A first model describes diffusion phenomena occurring inside the salami and the exchange phenomena involving the surface of the product and the environment. After the ripening, the salami are stored in waterproof packaging, consequently an additional model able to describe also the evaporation and condensation phenomena occurring between the salami surface and the air in the package, was developed. The moisture equilibrium between salami surface and conservation atmosphere is mainly ruled by the temperature changes during storage. Both models allow to analyze the history of the moisture content inside the salami and are parametrised on product size and maturation/storage conditions. The models were experimentally validated, comparing the numerical outputs of the simulations with experimental data, showing a good agreement.

Fatty acids alkyl esters (FAAEs) in extra virgin olive oils (EVOOs) are recognized markers of the quality and genuineness of the product. As a consequence of sugar fermentation in damaged olives stored under bad conditions or pectin enzymatic demethylation in overripe olives, ethyl and methyl derivatives of fatty acids are produced. Concentrations of FAAEs out of the legal limit for EVOO (EU Reg. 61/2011) can be accompanied by sensory defects as fusty, winey and musty, linked to the low quality of processed olives. The legal limit of FAAEs in EVOOs is fixed to 75 mgkg-1 and up to 150 mgkg-1 if the ratio between ethyl and methyl esters is less or equal to 1.5. Since the illegal practice of "mild deodorization" is able to remove volatile molecules responsible for the sensory defects without producing clear chemical markers, FAAEs assessment is recognized, at date, as an effective method to make this fraud useless and assure the technological authenticity EVOO. Given the commercial importance of the FAAEs assessment, a rapid and environmental friendly method based on the multivariate analysis of Time Domain Reflectometry (TDR) signals was proposed for a fast screening of the total amount of FAAEs. TDR is one of the techniques used to measure the dielectric properties of different kind of liquids. In the present research, Principal Component Analysis (PCA) and PLS (Partial Least Squares) regression were respectively performed in order to identify the TDR regions that better describe the variances of EVOO samples and to estimate FAAEs content. Main results indicated that PLS models are able to predict FAAEs content in terms of sum of fatty acid methyl esters and fatty acids ethyl esters, with good values of the coefficient of determination R2 (higher than 0.920 in test set validation). The ratio between ethyl and methyl esters was also statistically correlated with the TDR signals, but the prediction was not so good, so when the content of FAAEs is between 75 and 150 mgkg-1, at the time, the official chromatographic determination is mandatory.

In this work the results of a wide research concerning the “Quality in cup” of espresso coffee directly prepared in coffee shops (688) of six different geographic area of Italy (Central and Northern) performed during a period of over 10 years were discussed. In this way different process variables such as type of roasting plant, type of grinding-batcher plant, type of extraction machine (manual, automatic, semi-automatic), blend, water temperature and pressure, weight of powder and its compression inside the filter, were analysed before coffee extraction. Furthermore, the quality in cup was evaluated by measuring the most important indexes such as the consistency and the height of cream, pH, °Bx and volume of brew. Several experiment were performed in laboratory scale with the aim to evaluate the effects of possible uncontrolled variables during the coffee brew preparation in coffee shops. Over than 9000 data were then statistically elaborated by Anova analysis, Mann-Whitney test and Levene test. The Principal component analysis (PCA) of extraction process data and of quality parameters of espresso coffee was used in order to discriminate the quality characteristics of coffee brews in relation to the different geographic areas and to discriminate the significant differences among the years of the investigation (from 2000 to 2011). From results, the type of extraction plant and of grinding-batcher plant as well as a good training of bar operators emerged as the most affecting variables the quality of espresso coffee.

I metodi spettroscopici NIR e FT-IR supportati da avanzate tecniche statistiche (PCA, PLS) sono risultati essere in grado di discriminare campioni di P-R e campioni considerati non conformi (difettati e P-R con un contenuto in crosta superiore al 18%) in maniera veloce ed affidabile. I modelli predittivi PLS hanno messo in luce che è possibile stimare il contenuto di crosta dei campioni di P-R, con valori di R2 pari a 0.95 in validazione. I risultati ottenuti con le tecniche NIR e FT-IR sono in linea tra loro, a conferma dell’affidabilità dei metodi utilizzati.

The aim of the study was to simulate a hot-air-based treatment of the egg shell by a simplified finite element model. The calculated temperatures were compared with experimental data observed on an egg shell instrumented with thermocouples. A simple plant was used to make eggs roll while hot and cold air jets impinged the shell on opposite sides. The results have shown good agreement between calculated and observed temperatures on the inner part of the shell, despite the simplicity of the 2D numerical model. The observed temperature profiles, compatible both with albumen coagulation condition and shell pasteurization, support the hot air treatment as a possible and innovative surface decontamination technique for table eggs. PRACTICAL APPLICATIONS As hot-air decontamination is an innovative one, several tests will be necessary to assess the technique and to engineer the process. Unfortunately, each trial needs a number of microbial and quality tests requiring a remarkable amount of time and money. The numerical model made possible the testing of several thermal cycles, optimizing the value of the process parameters involved, reducing experimental effort. Moreover, the 2D model enhanced the advantages, with respect to the full 3D model, balancing an acceptable feasibility loss with much shorter calculus time.

Frutta di IV gamma confezionata, insieme ad un liquido di governo, in contenitori di materiale plastico esce dall’ambiente di lavorazione con temperatura al cuore pari a circa 0°C. Il trasporto avviene in vani refrigerati, ma soggetti a frequente ingresso di aria dall’esterno. Viene affrontato il problema del mantenimento di un livello di temperatura compatibile con una appropriata condizione di conservazione della frutta durante il trasferimento dallo stabilimento di produzione al cliente. In particolare sono studiate diverse possibili modifiche da effettuare al contenitore di trasporto al fine di mantenere una temperatura al cuore inferiore a 10°C. Lo studio è stato svolto tramite la costruzione di modelli numerici in grado di descrivere i fenomeni termici che intervengono durante la fase di trasporto del prodotto