Real-time monitoring of organic apple (var. Gala) during hot-air drying using near-infrared spectroscopy

Moscetti, Roberto; Raponi, Flavio; Ferri, Serena; Colantoni, Andrea; Monarca, Danilo; Massantini, Riccardo

doi:10.1016/j.jfoodeng.2017.11.023

Cited by 48 publications

(27 citation statements)

References 51 publications

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“…Moreover, to monitor the thermal treatment, POD is frequently used as indicator enzymes due to its higher thermal stability and easiness in being assayed. In fact, the POD inactivation allows the reasonable assumption that other quality-deteriorative enzymes are also inactivated [76,77]. Further, POD may be responsible for enhancement of degradation of phenols when coexisting with PPOs [14].…”

Section: Assessment Of Oxidative Enzymes Activity At Optimum Goalsmentioning

confidence: 99%

Optimisation of Physical and Chemical Treatments to Control Browning Development and Enzymatic Activity on Fresh-cut Apple Slices

Shrestha

Kulig

Moscetti

et al. 2020

Foods

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Optimisation of processing time and pre-treatments are crucial factors prior to apple drying to produce a high-quality product. The purpose of the present study was to test the utility of physical (hot-water, HWB and steam blanching, SB) and chemical (1% ascorbic acid, AA; and 1% citric acid, CA) treatments, alone or in combination in reducing surface discolouration as well as oxidative enzyme activity in apple slices (cv. Golden Delicious and Elstar) exposed to air at room temperature for 0, 30 and 60 min. The total colour change (ΔE) for Golden Delicious was equal to 2.38, 2.68, and 4.05 after 0, 30 and 60 min of air exposure, respectively. Dipping in AA solution (1% w/v) was found to be the best treatment to limit surface discolouration of both apple cultivars. The best heat treatments to inhibit polyphenol oxidase/peroxidase enzymes activity were 70 °C HWB for Golden Delicious and 60 °C HWB for Elstar slices, both in combination with a solution of 1% AA and 1% CA. The tested apple cultivars were found to require different treatments at minimum ambient air exposure to obtain the best surface colour condition.

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Section: Assessment Of Oxidative Enzymes Activity At Optimum Goalsmentioning

confidence: 99%

Optimisation of Physical and Chemical Treatments to Control Browning Development and Enzymatic Activity on Fresh-cut Apple Slices

Shrestha

Kulig

Moscetti

et al. 2020

Foods

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“…Here the parameters of each method are tuned by the traditional cross-validation methods. Not list all, the prediction results for the third quality variable 3 Y by the proposed WFPLS, SVR, and PLS are shown in Figure 4 As shown in Figure 4 (a), the predicted values by WFPLS exactly overlap the true values. The values predicted by the SVR and PLS methods have some deviations to the true values more or less (Figure 4 (b) and (c)).…”

Section: A Numerical Casementioning

confidence: 83%

Functional Soft Sensor Based on Spectra Data for Predicting Multiple Quality Variables

et al. 2020

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In many complex chemical processes, such as ethanol fermentation process, prediction of the multivariate quality variables based on spectra data presents a great challenge because the dimensions of the spectra far exceed their sampling number. To address this problem, the dimension reduction of the predictors is necessary. It can be conducted either by regressing on components or by smoothing methods with basis functions. Based on the functional data analysis methods, this work introduces a novel wavelet functional partial least squares (WFPLS), which combines both of the foregoing dimension-reduction approaches. The high-dimensional spectra can be well fitted by fewer wavelet basis functions in the proposed method. Using the proposed WFPLS method does not require the measured data to be linear and to be sampled on a regular basis. It will be proved that the proposed WFPLS method can be finally transferred into the traditional PLS method in computation. By comparison with the existing prediction methods, the advantages of the proposed method are well demonstrated via a numerical case and an ethanol fermentation experiment. INDEX TERMS Wavelet functional partial least squares, soft sensor, functional data analysis, spectra data analysis, active learning.

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“…As expected, the moisture content decreases gradually with drying time and the drying rate is higher at the highest temperature. [8][9][10] The drying time to reach the final moisture content of 0.11 g H2O/ g D.M were 360 min and 240 min at the drying air temperatures of 60 and 70 °C, respectively. ANOVA indicates significant effect of drying time on moisture content.…”

Section: Methodsmentioning

confidence: 99%

“…Many studies have been carried out estimating dried apple quality characteristics. [7][8][9][10] However, very few studies have been carried out in the organic sector. Thus, the aim of this study was to determine the impact of the drying temperature on the drying behaviour and colour parameters of organic apple slices, as well as to investigate quality metrics predictions such as moisture content and chromaticity using the visible/near-infrared (Vis/NIR) spectroscopy during the drying process.…”

Section: Introductionmentioning

confidence: 99%

Organic apples (cv. Elstar) quality evaluation during hot-air drying using Vis/NIR hyperspectral imaging

Shrestha

Moscetti

Crichton³

et al. 2018

Proceedings of 21th International Drying Symposium

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Organic dried apples are common snacks fulfilling functional as well as nutritional aspects. However, appearance of dried slices does not always satisfy consumer requirements, thus, improvements are needed. In this study, partial least squares (PLS) regression models were successfully developed to monitor changes in colour and moisture content in apple slices during the drying process over the Vis/NIR spectral range. The regression vector analysis results suggested that features at 580, 750 and 970 nm are better for predicting moisture content, while 580 and 680 nm allow to measure the (a*/b*) colour ratio. Keywords: Drying; Dried apple slices; Moisture content; Colour; PLSR modelling

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Real-time monitoring of organic apple (var. Gala) during hot-air drying using near-infrared spectroscopy

Cited by 48 publications

References 51 publications

Optimisation of Physical and Chemical Treatments to Control Browning Development and Enzymatic Activity on Fresh-cut Apple Slices

Optimisation of Physical and Chemical Treatments to Control Browning Development and Enzymatic Activity on Fresh-cut Apple Slices

Functional Soft Sensor Based on Spectra Data for Predicting Multiple Quality Variables

Organic apples (cv. Elstar) quality evaluation during hot-air drying using Vis/NIR hyperspectral imaging

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