Fast and accurate quality assessment of Raf tomatoes using NIRS technology

Torres, Irina; Pérez‐Marín, Dolores; Haba, María-José De la; Sánchez, María‐Teresa

doi:10.1016/j.postharvbio.2015.04.004

Cited by 31 publications

(28 citation statements)

References 24 publications

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“…However, Clément et al . and Torres et al . used NIRS technology to predict the color index in tomatoes using Varian Cary 500 UV–Vis–NIR (spectral range 400–1000 nm) and Perten DA‐7000 (spectral range 400–1700 nm) spectrophotometers, obtaining models whose predictive capacities (RPD cv = 2.81 and RPD cv = 2.23 respectively) were higher than those obtained here, which shows how difficult it is to take pepper color measurements during the ripening process on the plant given the irregular distribution of this parameter throughout ripening, as well as the convenience of using instruments that focus on the visible region of the spectrum.…”

Section: Resultscontrasting

confidence: 57%

“…15,19 No previous studies have been found in the scientific literature on measuring the color index (a*/b*) in peppers using NIRS technology, although values for a*/b* increase significantly during ripening due wileyonlinelibrary.com/jsfa to higher carotenoid levels, thus also providing a useful indicator of the fruit's ripeness. 28 However, Clément et al 29 and Torres et al 30 used NIRS technology to predict the color index in tomatoes using Varian Cary 500 UV-Vis-NIR (spectral range 400-1000 nm) and Perten DA-7000 (spectral range 400-1700 nm) spectrophotometers, obtaining models whose predictive capacities (RPD cv = 2.81 and DMC: dry matter content; N: number of samples; r 2 cv : coefficient of determination for cross-validation; RPD cv : ratio of the SD of the original data to SECV; SD: standard deviation; SECV: standard error of cross-validation; SEL: standard error of laboratory; SSC: soluble solid content; TA: titratable acidity.…”

Section: Prediction Of Color and Quality Parameters Using Mpls Regresmentioning

confidence: 99%

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In situ ripening stages monitoring of Lamuyo pepper using a new‐generation near‐infrared spectroscopy sensor

et al. 2020

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BACKGROUND Near‐infrared spectroscopy (NIRS) was used as a nondestructive sensor to assess the quality of freshly harvested Lamuyo peppers. One hundred and forty‐four Lamuyo peppers, which were in a range of colors (green, chocolate, orange, and red) when harvested, were analyzed. In this study, the evolution of the main quality parameters during the harvest period was analyzed. Additionally, NIRS predictive models using a portable manual spectrophotometer to evaluate quality parameters together with color index were developed. Moreover, two procedures for taking near‐infrared spectra were tested: (1) static, where point spectral readings were taken of around the equator of the fruit; (2) dynamic, where spectra were taken by scanning the entire length of the pepper. RESULTS Green peppers and those harvested at the beginning of the campaign presented significantly lower values (P < 0.05) of dry matter, soluble solid contents, and titratable acidity, whereas those with red coloration and those harvested at the end of the campaign showed significantly higher values of these three quality parameters (P < 0.05). The predictive capacity of the NIRS models showed that the static mode proved to be the most suitable for measuring the quality of Lamuyo peppers. CONCLUSIONS The viability of NIRS for measuring dry matter content and soluble solid contents in situ, using a new‐generation NIRS sensor, was demonstrated. However, the high water content, the irregular shape of the fruit, and the fact that it is hollow inside all point to the need for using larger samples sets so as to increase the robustness of the models obtained. © 2019 Society of Chemical Industry

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Section: Resultscontrasting

confidence: 57%

Section: Prediction Of Color and Quality Parameters Using Mpls Regresmentioning

confidence: 99%

In situ ripening stages monitoring of Lamuyo pepper using a new‐generation near‐infrared spectroscopy sensor

et al. 2020

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“…In this way, the consumer will receive accurate information about the differences in quality between vegetables produced using different agronomic techniques and about their origin. In this field, near‐infrared (NIR) spectroscopy has proved to be an ideal way of providing authentication/certification of raw horticultural materials produced using different types of agricultural methods, as well as for the authentication of varieties …”

Section: Introductionmentioning

confidence: 99%

Rapid, simultaneous, and in situ authentication and quality assessment of intact bell peppers using near‐infrared spectroscopy technology

et al. 2018

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The results showed that NIR spectroscopy can be used successfully for predicting the growing systems used in bell pepper production, which is of particular value to guarantee the authentication of outdoor-grown peppers. Additionally, the results showed that NIR spectroscopy can be used simultaneously as a rapid preliminary screening technique to measure quality. © 2018 Society of Chemical Industry.

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“…In particular, because fruits and vegetables have a short shelf life, economic losses can be reduced by rapid techniques. When the literature is examined, it is seen that one of the most promising techniques is the near‐infrared spectroscopy (NIRS) technique, which has been applied successfully for qualitative and quantitative analyses of quality control of fruits and vegetables . This technique has a low operating cost compared to traditional techniques and allows analysis in a short time.…”

Section: Introductionmentioning

confidence: 99%

“…When the literature is examined, it is seen that one of the most promising techniques is the near-infrared spectroscopy (NIRS) technique, which has been applied successfully for qualitative and quantitative analyses of quality control of fruits and vegetables. [18][19][20][21] This technique has a low operating cost compared to traditional techniques and allows analysis in a short time. It can also be used online in processing lines as a method that requires little or no sample preparation.…”

Section: Introductionmentioning

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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Fast and accurate quality assessment of Raf tomatoes using NIRS technology

Cited by 31 publications

References 24 publications

In situ ripening stages monitoring of Lamuyo pepper using a new‐generation near‐infrared spectroscopy sensor

In situ ripening stages monitoring of Lamuyo pepper using a new‐generation near‐infrared spectroscopy sensor

Rapid, simultaneous, and in situ authentication and quality assessment of intact bell peppers using near‐infrared spectroscopy technology

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

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