The use of visible and near infrared spectroscopy for evaluating passion fruit postharvest quality

Maniwara, Phonkrit; Nakano, K.; Boonyakiat, Danai; Ohashi, Shintaroh; Hiroi, Masaru; Tohyama, Tadahiro

doi:10.1016/j.jfoodeng.2014.06.028

Cited by 83 publications

(47 citation statements)

References 34 publications

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“…After the calibration model had been developed, it was then used to predict the composition/property of samples in the prediction set. Correlation coefficient (r), standard error for the calibration and prediction data sets (SEC and SEP), root mean square errors of cross validation (RMSECV), bias (predicted fault) and the ratio of sample standard deviation to standard error of prediction (RPD) were calculated and used to evaluate the calibration model (Lu, 2001;Maniwara et al, 2014).…”

Section: Spectra Processing and Chemometric Models Developmentmentioning

confidence: 99%

Measurement of moisture, soluble solids, sucrose content and mechanical properties in sugar beet using portable visible and near-infrared spectroscopy

Pan

Zhu

et al. 2015

Postharvest Biology and Technology

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Section: Spectra Processing and Chemometric Models Developmentmentioning

confidence: 99%

Measurement of moisture, soluble solids, sucrose content and mechanical properties in sugar beet using portable visible and near-infrared spectroscopy

Pan

Zhu

et al. 2015

Postharvest Biology and Technology

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“…To obtain different concentrations, 32 different solutions (0, 0.01, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.5, 2, 2.5, 3, 3. 5,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20 times the prescribed dose) were prepared.…”

Section: Strawberry Collection and Pesticide Applicationmentioning

confidence: 99%

“…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%

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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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“…Vis-NIR spectroscopy applied to the qualitative or quantitative analysis of fruit components has been recently reported (Xie et al 2009;Menesatti et al 2010;Maniwara et al 2014). Equipped with a fiber sensor probe (one kind of instrumental attachments), Vis-NIR spectrometers can capture the diffuse reflectance spectrum of an original nondestructive fruit.…”

Section: Introductionmentioning

confidence: 99%

Rapid Detection of Surface Color of Shatian Pomelo Using Vis-NIR Spectrometry for the Identification of Maturity

Chen

Tang

et al. 2015

Food Anal. Methods

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Shatian pomelo is one kind of high-quality fruits grown in south China. Modern agricultural planting technology for Shatian pomelo closely relates to the rapid identification of its maturity. As surface color reflects the maturity of fruits, quantitative determination on the color indices of L*, a*, and b* is significant for maturity judgment. Chemoinformatic models were applied for quantitative detection of L*, a*, and b* for Shatian pomelo, by using visible and near-infrared (Vis-NIR) spectrometry. To enhance the analytical accuracy and model stability, we proposed the combined use of moving window partial least squares (MWPLS) and modified optical path length estimation and correction (MOPLEC) to search for high-signal wavelength combinations, in fully optimizing the modeling parameters. Results indicated that the chemoinformatics that we proposed performed well for nondestructive evaluations of the maturity of Shatian pomelo. This technology is expected to be utilized for quality evaluations of some other agricultural and planting fruits.

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The use of visible and near infrared spectroscopy for evaluating passion fruit postharvest quality

Cited by 83 publications

References 34 publications

Measurement of moisture, soluble solids, sucrose content and mechanical properties in sugar beet using portable visible and near-infrared spectroscopy

Measurement of moisture, soluble solids, sucrose content and mechanical properties in sugar beet using portable visible and near-infrared spectroscopy

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

Rapid Detection of Surface Color of Shatian Pomelo Using Vis-NIR Spectrometry for the Identification of Maturity

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