Class‐modeling approach to <scp>PTR‐TOFMS</scp> data: a peppers case study

Taiti, Cosimo; Costa, Corrado; Menesatti, Paolo; Comparini, Diego; Bazihizina, Nadia; Azzarello, Elisa; Masi, Elisa; Mancuso, Stefano

doi:10.1002/jsfa.6761

Cited by 37 publications

(42 citation statements)

References 35 publications

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“…The partitioning of the models for M3, which include all the sampling times, was conducted optimally by choosing the Euclidean distances based on the algorithm of Kennard & Stone (1969) that selects objects without the a priori knowledge of a regression model. A summary of the relative importance of the Xvariables for both Y and X model parts is given by Variable Importance in the Projection (VIP - Taiti et al 2015, Infantino et al 2015. VIP scores estimate the importance of each variable in the PLS-based models.…”

Section: Discussionmentioning

confidence: 99%

Characterization of VOC emission profile of different wood species during moisture cycles

Sassoli¹,

Taiti²,

Nissim³

et al. 2017

iForest

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This study addresses the characterization of volatile organic compounds (VOCs) emitted by samples of 13 different wood species, belonging to both softwoods and hardwoods groups, regularly measured at different intervals of time, after the first measurement on green wood. The same wood specimens were subjected to several cycles of water desorption and adsorption, assuming that moisture variation might play a role in both the formation and emission of VOCs. Proton Transfer Reaction-Time of Flight-Mass Spectrometry (PTR-TOF-MS) was used as a tool to characterize the emission of VOCs. Coupled with a multivariate class-modelling approach, this tool was able to discriminate between groups (softwood and hardwood) and in some cases between different species. However, results showed that the discriminant capacity of VOCs emission to separate species and families rapidly decreases after the first cycles of moisture variation in wood. The green wood was characterized by a richness of volatile compounds, whereas, after only the first dry cycle, wood emitted a more restricted group of compounds. We hypothesized that most of these VOCs might have originated from structural changes and degradation processes that involve the main polymers (particularly hemicellulose) constituting the cell wall of wooden cells. The results obtained are in agreement with the physical and chemical modification processes that characterize wood ageing.

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Section: Discussionmentioning

confidence: 99%

Characterization of VOC emission profile of different wood species during moisture cycles

Sassoli¹,

Taiti²,

Nissim³

et al. 2017

iForest

View full text Add to dashboard Cite

show abstract

“…In PLS-R and PLS-DA methods, a summary of the relative importance of the X-variables for both Y and X model parts is given by Variable Importance in the Projection (VIP) [31,32]. It is a weighted sum of squares of the PLS weights, taking into account the amount of explained Y-variance in each PLS component [33].…”

Section: Multivariate Modelingmentioning

confidence: 99%

Automated determination of poplar chip size distribution based on combined image and multivariate analyses

Febbi

Menesatti²,

Costa³

et al. 2015

Biomass and Bioenergy

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“…The independent variables (X-block) datasets were standardised using an autoscale algorithm (i.e., centers columns to zero mean and scales to unit variance). For each PLS model a summary of the relative importance of the independent variables (Y-block) to predict the dependent one is given by variable importance in the projection (VIP) (Febbi et al, 2015;Taiti et al, 2015). The VIP scores estimate the importance of each variable in the PLS-based models and were calculated according to Chong & Jun (2005).…”

Section: Multivariate Modellingmentioning

confidence: 99%

An innovative multivariate tool for fuel consumption and costs estimation of agricultural operations

Guerrieri¹,

Fedrizzi²,

Antonucci³

et al. 2017

Span. j. agric. res.

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The estimation of operating costs of agricultural and forestry machineries is a key factor in both planning agricultural policies and farm management. Few works have tried to estimate operating costs and the produced models are normally based on deterministic approaches. Conversely, in the statistical model randomness is present and variable states are not described by unique values, but rather by probability distributions. In this study, for the first time, a multivariate statistical model based on Partial Least Squares (PLS) was adopted to predict the fuel consumption and costs of six agricultural operations such as: ploughing, harrowing, fertilization, sowing, weed control and shredding. The prediction was conducted on two steps: first of all few initial selected parameters (time per surface-area unit, maximum engine power, purchase price of the tractor and purchase price of the operating machinery) were used to estimate the fuel consumption; then the predicted fuel consumption together with the initial parameters were used to estimate the operational costs. Since the obtained models were based on an input dataset very heterogeneous, these resulted to be extremely efficient and so generalizable and robust. In details the results show prediction values in the test with r always ≥ 0.91. Thus, the approach may results extremely useful for both farmers (in terms of economic advantages) and at institutional level (representing an innovative and efficient tool for planning future Rural Development Programmes and the Common Agricultural Policy). In light of these advantages the proposed approach may as well be implemented on a web platform and made available to all the stakeholders.

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Class‐modeling approach to PTR‐TOFMS data: a peppers case study

Abstract: Based on the promising results, the possibility of introducing multivariate class-modeling techniques, different from the classification approaches, in the field of volatile compounds analyses is discussed.

Cited by 37 publications

References 35 publications

Characterization of VOC emission profile of different wood species during moisture cycles

Characterization of VOC emission profile of different wood species during moisture cycles

Automated determination of poplar chip size distribution based on combined image and multivariate analyses

An innovative multivariate tool for fuel consumption and costs estimation of agricultural operations

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