1,721,025 research outputs found
Inversion of a numerical model to estimate the effective moisture diffusivity in baking cake
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In field Vis/NIR hyperspectral imaging to measure soluble solids content of wine grape barriers during ripening
Full text linkMonitoring the quality attributes of grapes is a practice that allows to check the grapes' state of ripeness and to decide when it is appropriate to proceed with the harvest. In the present study, a non-destructive method based on hyperspectral imaging (HSI) technology was developed. Analyses were carried out directly in the field using a Vis/NIR (400-1000 nm) hyperspectral camera (HSC) between the rows of 'Sangiovese' (Vitis vinifera L.) vineyard destined for wine production. One vineyard row was analyzed on 13 different days. During the trials, 33 berries were collected and the soluble solids content (SSC) expressed in terms of degrees Brix (degrees Bx) was measured by a portable digital refractometer. The mean spectra of the selected berries were extracted from each hyperspectral (HS) image. The pre-treated mean spectra were used to predict the SSC of the berries by means of partial least squares (PLS) regression, obtaining a value of R-2 = 0.75 in cross-validation, with RMSECV = 0.84 degrees Bx. The present study shows the potential of the use of HSI technology directly in the field through proximal measurements under natural light conditions for the prediction of the SSC quality attribute of grapes
Potential of the on-field hyperspectral imaging to measure the sugar content in grape.
Full text linkRipeness evaluation of kiwifruit by hyperspectral imaging
Full text linkRapid, non-destructive fruit sorting techniques are increasingly being adopted to ensure that producers, industry, and consumers receive products that meet their quality requirements. Quality attributes typically used to assess fruit ripeness include soluble solids content (SSC) and flesh firmness (FF). In this study, hyperspectral imaging operating at 400–1000 nm (Vis/NIR) was adopted to evaluate the ripeness degree of ‘Hayward’ kiwifruit. Partial least square (PLS) regression models were developed to estimate SSC and FF, while two different types of PLS discriminant analysis (PLS-DA) were used to classify samples according to three repining classes (defined on the base of SCC and FF values). To reduce the computation complexity, and simplify the calibration models, two variable selection methods (genetic algorithm GA, and variable importance in projection VIP) were adopted. For SSC, the prediction R2 values ranged from 0.85 (RMSE = 1.10 °Brix) to 0.94 (RMSE = 0.73 °Brix), and for FF from 0.82 (RMSE = 14.51 N) to 0.92 (RMSE = 9.87 N). Classification sensitivity reached values of 97% and 93%, for the model considering the SCC and FF classes, respectively. Prediction and classification performances remained substantially unchanged by reducing the number of wavelengths. Therefore, hyperspectral imaging appears to be suitable for prediction of kiwi quality attributes and their classification
Pallets and bags
No full textPackaging can be an important resource for improving efficiency in the supply
chain and advertising products and companies. The main processes of the supply
chain, such as storage and transportation, are usually facilitated by reusable
transport items (RTIs) (Zhou et al., 2018). A unit load is an assemblage into
which a number of individual items are combined, typically on a pallet, to facil itate material handling and storage operations. With logistic and technology
development demanding express transportation service and commerce on a
global scale, the unit mode is widely implemented in logistics. Integrated pack aging, such as pallets, container cages, and bags, is employed for a cheap, effi cient, and convenient unitized logistics mode (Zhou et al., 2018).
Packaging can be thought of as composed of three parts: the primary pack age, in contact with the product; the secondary package, usually a shipping con tainer, case or bags to group packages; and the tertiary package, such as a pallet,
which has the function of a load unifier for transportation, storage, and distri bution (Twede et al., 2007). Considering handling and transport, the pallet is
the most used type of packaging worldwide. Rarely, it could be found that a
logistic service is provided by the company without considering pallets. Despite
the fundamental role of pallets, they are one of the most neglected constituents
within handling transactions (Clarke, 2004). Generally, packaging is widely
studied and designed, but only a brief description of pallets is given, although they
can be considered the joint component between packed goods and transport in
order to be efficient for handling management and cost reduction (Clarke, 2004).
A suitable definition of a pallet is: “Pallet is a portable, rigid platform used
as a base for assembling, storing, stacking, handling, and transporting goods”
(Bouffier et al., 1996). As a standardized platform for unit loads, pallets are
widely utilized in manufacturing facilities, warehouses and distribution centers, and stores. Many pallets are designed to be repairable and reusable, so they can
be reused for several shipping cycles.
Pallets in circulation can be considered as trade indicators of global eco nomic trends. If the economy is strong, the demand for goods increases, which
translates to a larger demand for pallets (Accorsi et al., 2019). There are roughly
5 billion pallets in use worldwide, and this value is anticipated to increase over
the next 5 years (Murray, 2021). Although 95% of the produced pallets are made
of wood, the use of nonwooden pallets, such as metal and plastic pallets, is
increasing. For the food industry, nonwooden pallets are often used in applica tions where hygiene is a concern (Ibrahim, 2019).
Several associations, such as the US Grocery Manufacturers Association
(GMA), the Canadian Pallet Council (CPC), and the European Pallet Associa tion (EPAL), provide directives and good practices to use, collect, repair, and
return pallets. This chapter summarizes the use of pallets and bags for unit load
operations and provides a detailed description of the manufacturing methods,
materials, tests, cleaning operations, requirements, and supply chain management considerations for pallets
Numerical modeling of heat and mass transfer during coffee roasting process
No full textIn this work a numerical model, based on a 3D geometry, able to describe the heat and moisture transfer inside a coffee bean during the roasting process, was developed. The model makes reference to a rotating cylinder roaster in natural convection conditions.
For the multiphysics model development heat and mass transfer equations inside the coffee bean were numerically solved using a finite element technique. Two domain geometries were tested. One simplified, based on a simple semi-ellipsis, and one made acquiring the shape of an Arabica coffee bean using a 3D scanner. To validate the numerical model, green coffee bean was singularly roasted using a rotating drum roasters prototype. The calculated moisture concentration and time–temperature curves were then compared with the observed data.
The calculated temperature values, in the centre of the bean, appear to be in good agreement with those measured inserting thermocouples into the coffee bean (RMSE 5.97 °C). Similarly the calculated volume averaged moisture was in good agreement with the experimental data (RMSE 264.251 mol/m3) over the entire time span. This model can be useful to optimise the roasting process control
Study of a Rapid Untargeted Chromatographic Approach to Discriminate Virgin Olive Oils with a different Geographical Origin
Full text linkCompliance with EU vs. extra-EU labelled geographical provenance in virgin olive oils: A rapid untargeted chromatographic approach based on volatile compounds
Full text linkMany studies have shown that geographic origin is one of the most influencing factors in consumers’ choice of
olive oil. To avoid misleading consumers, European regulation has established specific rules to report the geographical
origin of extra virgin (EVOOs) and virgin olive oils (VOOs) on the product label, even if an official
analytical procedure to verify the origin has not been yet defined. In this work, a flash gas chromatography
(FGC) untargeted approach based on volatile compounds, followed by a chemometric data analysis, is proposed
for discrimination of EVOOs and VOOs according to their geographical origin (EU and extra-EU). A set of 210
samples was analyzed and two different classification techniques were used, one linear (Partial Least Square-
Discriminant Analysis, PLS-DA) and one non-linear (Artificial Neural Network, ANN). The two models were also
validated using an external data set. Satisfactory results were obtained for both chemometric approaches: with
PLS-DA, 89% and 81% of EU and extra-EU samples, respectively, were correctly classified; for ANN, the percentages
were 92% and 88%, respectively. These results confirm the reliability of the method as a rapid approach
to discriminate EVOOs and VOOs according to their geographical provenance
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