Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review

Nicolaı̈, Bart; Beullens, Katrien; Bobelyn, Els; Peirs, Ann; Saeys, Wouter; Theron, Karen I.; Lammertyn, Jeroen

doi:10.1016/j.postharvbio.2007.06.024

Cited by 1,827 publications

(1,372 citation statements)

References 141 publications

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“…Model for predicting soluble solids presented a very satisfactory performance, with a value of Rcal of 0.91, RMSEC of 0.77°Brix, while the value of Rpred was found to be 0.88, with RMSEP of 0.95°Brix. As for residual prediction deviation, the obtained value close to 2 (1.92) indicates that that coarse quantitative predictions are possible by using the model (Nicolaï et al, 2007). These results were similar to those reported in the studies of Cao et al (2010) in which the TSS of grape berries belonging to three different varieties were measured by using 2 different model development techniques i.e., PLS and genetic algorithm coupled with least square support vector machine (GA-LS-SVM).…”

Section: Articlesupporting

confidence: 85%

Spectra evolution over on-vine holding of Italia table grapes: prediction of maturity and discrimination for harvest times using a Vis-NIR hyperspectral device

Piazzolla

Amodio

Colelli

2017

J Agricult Engineer

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Measurement of certain grape quality parameters (sugars, acidity, and pH-value) is essential for the determination of the optimum harvest time. Non-destructive analytical techniques, including near infrared (NIR) spectroscopy, can be valid alternatives to traditional analytical methods for the determination of maturity indexes, enabling the possibility of on-field applications. This work aims to study the reliability to monitor spectra changes related with ripening of table grapes and to select optimal wavelengths for the discrimination of bunches from different harvests, in addition to the prediction of total soluble solids, pH, titratable acidity, phenols and antioxidant activity of table grapes. Grapes were harvested four times from the same plants at day 0 (I HT), and after 11 (II HT), 27 (III HT) and 48 (IV HT) days. Spectra were acquired from the images obtained using a spectral scanner Vis-NIR (ver 1.4.; DV Srl, Padova, Italy), with a detector in the region between 400-1000 nm principal component analysis was used to remove outliers followed by spectra pre-treatment. The best prediction model was achieved for soluble solids with the regression coefficient values of 0.91 for calibration and 0.88 for validation followed by titratable acidity (0.71 and 0.78) and antioxidant activity (0.68 and 0.62). In addition an excellent correlation was observed between spectra and days before harvest (R 2 of 0.98 for calibration and prediction models) indicating that is possible to relate spectra changes with ripening, leading also to the effective discrimination of the fruits from the different harvest times. The results showed that this technique may be a valid support to select the optimal harvest time also based on the prediction of the maturity related constituents.

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Section: Articlesupporting

confidence: 85%

Spectra evolution over on-vine holding of Italia table grapes: prediction of maturity and discrimination for harvest times using a Vis-NIR hyperspectral device

Piazzolla

Amodio

Colelli

2017

J Agricult Engineer

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“…Furthermore, if viewed from the value of RPD, it is still above two. According to Nicolai [9] the value of RPD within 2-3 indicates that the model includes good model performance.…”

Section: Predict Cupping Scorementioning

confidence: 99%

Estimation of Sensory Analysis Cupping Test Arabica Coffee Using NIR Spectroscopy

Safrizal

Sutrisno

Lilik

et al. 2018

IOP Conf. Ser.: Earth Environ. Sci.

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Abstract. Flavors have become the most important coffee quality parameters now day, many coffee consuming countries require certain taste scores for the coffee to be ordered, the currently used cupping method of appraisal is the method designed by The Specialty Coffee Association Of America (SCAA), from several previous studies was found that Near-Infrared Spectroscopy (NIRS) can be used to detect chemical composition of certain materials including those associated with flavor so it is possible also to be applied to coffee powder. The aim of this research is to get correlation between NIRS spectrum with cupping scoring by tester, then look at the possibility of testing coffee taste sensors using NIRS spectrum. The coffee samples were taken from various places, altitudes and postharvest handling methods, then the samples were prepared following the SCAA protocol, for sensory analysis was done in two ways, with the expert tester and with the NIRS test. The calibration between both found that Without pretreatment using PLS get RMSE cross validation 6.14, using Multiplicative Scatter Correction spectra obtained RMSE cross validation 5.43, the best RMSE cross-validation was 1.73 achieved by de-trending correction, NIRS can be used to predict the score of cupping.

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“…Among those, mean centering of the spectra is to remove the absolute baseline. Scaling of the spectra, in addition, involves dividing each wavelength data by its standard deviation, which allows each wavelength to have the same importance during calibration [5]. However, scaling is not recommended when most of the spectra do not contain useful information.…”

Section: Spectral Pretreatmentmentioning

confidence: 99%

“…It provides useful information about the chemical composition of the sample. The capability of predicting certain quality characteristics or attributes of the samples by NIR has been evaluated extensively in many research areas [3,5]. Such calibration models have been built based on simple linear regression techniques.…”

Section: Introductionmentioning

confidence: 99%

Comparative Study of NIR-based Prediction Methods for Biomass Weight Loss Profiles

Cho¹,

Liu²

2012

Clean Technology

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: Biomass has become a major feedstock for bioenergy and other bio-based products because of its renewability and environmental benefits. Various researches have been done in the prediction of crucial characteristics of biomass, including the active utilization of spectroscopy data. Near infrared (NIR) spectroscopy has been widely used because of its attractive features: it's non-destructive and cost-effective producing fast and reliable analysis results. This work developed the multivariate statistical scheme for predicting weight loss profiles based on the utilization of NIR spectra data measured for six lignocellulosic biomass types. Wavelet analysis was used as a compression tool to suppress irrelevant noise and to select features or wavelengths that better explain NIR data. The developed scheme was demonstrated using real NIR data sets, in which different prediction models were evaluated in terms of prediction performance. In addition, the benefits of using right pretreatment of NIR spectra were also given. In our case, it turned out that compression of high-dimensional NIR spectra by wavelet and then PLS modeling yielded more reliable prediction results without handling full set of noisy data. This work showed that the developed scheme can be easily applied for rapid analysis of biomass.

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Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review

Cited by 1,827 publications

References 141 publications

Spectra evolution over on-vine holding of Italia table grapes: prediction of maturity and discrimination for harvest times using a Vis-NIR hyperspectral device

Spectra evolution over on-vine holding of Italia table grapes: prediction of maturity and discrimination for harvest times using a Vis-NIR hyperspectral device

Estimation of Sensory Analysis Cupping Test Arabica Coffee Using NIR Spectroscopy

Comparative Study of NIR-based Prediction Methods for Biomass Weight Loss Profiles

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