Potential of NIR spectroscopy for predicting internal quality and discriminating among strawberry fruits from different production systems

Amodio, Maria Luisa; Ceglie, F.G.; Chaudhry, Muhammad Mudassir Arif; Piazzolla, Francesca; Colelli, G.

doi:10.1016/j.postharvbio.2016.11.013

Cited by 101 publications

(66 citation statements)

References 36 publications

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“…Thus, the SSC of strawberries might be predicted non‐destructively from the fruit spectra. These results are consistent with the results of previous studies in which NIR or VIS–NIR spectra were used successfully to determine SSC in strawberries . Moreover, the results of the present study also show that SSC of strawberry juices may be predicted directly from their NIR spectra.…”

Section: Resultssupporting

confidence: 93%

“…Using the respective model, the TPC content in squeezed juice may be predicted from the UV–VIS–NIR spectra of the juice itself, or non‐destructively from the intact fruit NIR spectra. To date, only one study was reported on the determination of phenols content in strawberries using NIR spectra of fruit . However, the PLS model was characterized by low predictive ability (R 2 P = 0.45, RPD = 1.45).…”

Section: Resultsmentioning

confidence: 99%

“…Several studies have demonstrated the applicability of spectroscopic methods, mainly NIR or NIR combined with VIS spectroscopy, for testing the quality of strawberry fruit. Spectroscopy in the NIR range was successfully used to predict SSC, firmness, titratable acidity, pH, and color parameters . Discrimination between strawberries from different varieties and farming systems was reported .…”

Section: Introductionmentioning

confidence: 99%

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Non‐destructive determination of strawberry fruit and juice quality parameters using ultraviolet, visible, and near‐infrared spectroscopy

et al. 2019

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BACKGROUND The development of rapid methods for the determination of the soluble solids content (SSC) and total phenolic content (TPC) in fruit juices is of great interest. Soluble solids content is related to sensory attributes, whereas TPC is related to the antioxidant capacity of juices. The aim of this study was to develop and optimize the calibration models for the prediction of the SSC and TPC of strawberry juices from the spectra of fruit and juices. RESULTS Near infrared (NIR) spectra were measured for strawberry fruit and ultraviolet (UV), visible (VIS), and NIR spectra were measured for juices. The partial least squares regression models were validated using the test sample set and their predictive ability was evaluated on the basis of determination coefficients (R2P) and root mean square error of prediction (RMSEP). For SSC the models with high predictive ability were obtained using spectra of fruit (R2P = 0.929, RMSEP = 0.46%) or juices (R2P = 0.979, RMSEP = 0.25%) in the NIR range. The optimal models for TPC were obtained using NIR spectra of fruit (R2P = 0.834, RMSEP = 130.8 mg GA L−1) or UV–VIS–NIR spectra of juices (R2P = 0.844, RMSEP = 126.7 mg GA L−1). CONCLUSION The results show the potential of spectroscopy for predicting quality parameters of strawberry juices from the juice spectra itself or non‐destructively from the fruit spectra. They may contribute to the development of fruit sorting systems to optimize their use in juice production, as well as fast‐screening methods for quality control of juices. © 2019 Society of Chemical Industry

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Section: Resultssupporting

confidence: 93%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Non‐destructive determination of strawberry fruit and juice quality parameters using ultraviolet, visible, and near‐infrared spectroscopy

et al. 2019

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“…(b) with bands highlighted. These vibrations were identified according to the literature . Accordingly, the peak reaching a maximum at 5240 cm −1 shows the first overtone of the O─H group.…”

Section: Resultsmentioning

confidence: 99%

“…, with the maximum wavelengths of the absorption peaks highlighted. These peaks were identified according to the literature . Accordingly, the absorption at 10 433 cm −1 corresponded to O─H bonds from water and carbohydrate.…”

Section: Resultsmentioning

confidence: 99%

Determination of pesticide residual levels in strawberry (Fragaria) by near‐infrared spectroscopy

2020

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BACKGROUND In this study, an infrared‐based prediction method was developed for easy, fast and non‐destructive detection of pesticide residue levels measured by reference analysis in strawberry (Fragaria × ananassa Duch, cv. Albion) samples using near‐infrared spectroscopy and demonstrating its potential alternative or complementary use instead of traditional pesticide determination methods. Strawberries of Albion variety, which were supplied directly from greenhouses, were used as the study material. A total of 60 batch sample groups, each consisting of eight strawberries, was formed, and each group was treated with a commercial pesticide at different concentrations (26.7% boscalid + 6.7% pyraclostrobin) and varying residual levels were obtained in strawberry batches. The strawberry samples with pesticide residuals were used both to collect near‐infrared spectra and to determine reference pesticide levels, applying QuEChERS (quick, easy, cheap, rugged, safe) extraction, followed by liquid chromatographic–mass spectrometric analysis. RESULTS AND CONCLUSION Partial least squares regression (PLSR) models were developed for boscalid and pyraclostrobin active substances. During model development, the samples were randomly divided into two groups as calibration (n = 48) and validation (n = 12) sets. A calibration model was developed for each active substance, and then the models were validated using cross‐validation and external sets. Performance evaluation of the PLSR models was evaluated based on the residual predictive deviation (RPD) of each model. An RPD of 2.28 was obtained for boscalid, while it was 2.31 for pyraclostrobin. These results indicate that the developed models have reasonable predictive power. © 2019 Society of Chemical Industry

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The Use of Non‐destructive Techniques to Assess the Nutritional Content of Fruits and Vegetables

Amodio

Chaudhry

Colelli

2017

Fruit and Vegetable Phytochemicals

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Potential of NIR spectroscopy for predicting internal quality and discriminating among strawberry fruits from different production systems

Cited by 101 publications

References 36 publications

Non‐destructive determination of strawberry fruit and juice quality parameters using ultraviolet, visible, and near‐infrared spectroscopy

Non‐destructive determination of strawberry fruit and juice quality parameters using ultraviolet, visible, and near‐infrared spectroscopy

Determination of pesticide residual levels in strawberry (Fragaria) by near‐infrared spectroscopy

The Use of Non‐destructive Techniques to Assess the Nutritional Content of Fruits and Vegetables

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