scholarly journals Application of visible-near infrared spectroscopy to evaluate the quality of button mushrooms

2018 ◽  
Vol 27 (1) ◽  
pp. 38-45 ◽  
Author(s):  
Valentina Giovenzana ◽  
Alessio Tugnolo ◽  
Andrea Casson ◽  
Riccardo Guidetti ◽  
Roberto Beghi

The Agaricus bisporus mushroom is one of the most cultivated and consumed mushrooms in the world, thanks to its delicacy, nutritional value and flavour. The quality evaluation of the A. bisporus during the harvest is generally established by a visual check by trained operators. This method complies with the request of the Distribution Channel (DC) to retailers and guarantees very low physical damage to the mushrooms; nevertheless, it is subjective and it does not guarantee the highest quality standard for the consumer. The aim of this study was to test the use of visible/near infrared (vis/NIR) reflectance spectroscopy (400–1000 nm) to objectively evaluate the quality parameters of A. bisporus mushrooms. A total of 167 samples of A. bisporus mushrooms were harvested according to the main DC purchasing standards. The vis/NIR analyses were performed the day of sampling just before the physico-chemical analyses (sizes, firmness, soluble solids content and moisture content) used as reference quality parameters. The vis/NIR spectra were correlated to reference measures in order to build predictive models using the partial least squares regression method. Calculated models gave positive results regarding the prediction of the moisture content (r2(pred) = 0.78) and firmness (r2(pred) = 0.78). Results of this explorative study could be considered encouraging and demonstrate the applicability of vis/NIR spectroscopy on A. bisporus as a rapid technique (i) to monitor the productive process directly at the company, (ii) to standardize the harvest moment, and (iii) to support DC’s buyers’ choices, nowadays exclusively based on product external characteristics.

Foods ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 441 ◽  
Author(s):  
Manuela Mancini ◽  
Luca Mazzoni ◽  
Francesco Gagliardi ◽  
Francesca Balducci ◽  
Daniele Duca ◽  
...  

The determination of strawberry fruit quality through the traditional destructive lab techniques has some limitations related to the amplitude of the samples, the timing and the applicability along all phases of the supply chain. The aim of this study was to determine the main qualitative characteristics through traditional lab destructive techniques and Near Infrared Spectroscopy (NIR) in fruits of five strawberry genotypes. Principal Component Analysis (PCA) was applied to search for spectral differences among all the collected samples. A Partial Least Squares regression (PLS) technique was computed in order to predict the quality parameters of interest. The PLS model for the soluble solids content prediction was the best performing—in fact, it is a robust and reliable model and the validation values suggested possibilities for its use in quality applications. A suitable PLS model is also obtained for the firmness prediction—the validation values tend to worsen slightly but can still be accepted in screening applications. NIR spectroscopy represents an important alternative to destructive techniques, using the infrared region of the electromagnetic spectrum to investigate in a non-destructive way the chemical–physical properties of the samples, finding remarkable applications in the agro-food market.


2006 ◽  
Vol 57 (4) ◽  
pp. 403 ◽  
Author(s):  
Robert L. Long ◽  
Kerry B. Walsh

The imposition of a minimum total soluble solids (TSS) value as a quality standard for orange-flesh netted melon fruit (Cucumis melo L. reticulatus group) requires either a batch sampling procedure (i.e. the estimation of the mean and standard deviation of a population), or the individual assessment of fruit [e.g. using a non-destructive procedure such as near infrared (NIR) spectroscopy]. Several potential limitations to the NIR assessment of fruit, including the variation in TSS within fruit and the effect of fruit storage conditions on the robustness of calibration models, were considered in this study. Outer mesocarp TSS was 3 TSS units higher at the stylar end of the fruit compared with the stem end, and the TSS of inner mesocarp was higher than outer tissue and more uniform across spatial positions. The linear relationship between the outer 10 mm and the subsequent middle 10 mm of tissue varied with fruit maturity [e.g. 42 days before harvest (DBH), r 2 = 0.8; 13 DBH, r 2 = 0.4; 0 DBH, r 2 = 0.7], and with cultivars (at fruit maturity, Eastern Star 2001 r 2 = 0.88; Malibu 2001 r 2 = 0.59). This relationship notably affected NIR calibration performance (e.g. based on inner mesocarp TSS; R c 2 = 0.80, root mean standard error of cross-validation (RMSECV) = 0.65, and R c 2 = 0.41, RMSECV = 0.88 for mature Eastern Star and Malibu fruit, respectively). Cold storage of fruit (0–14 days at 5°C) did not affect NIR model performance. Model performance was equivalent when based on either that part of the fruit in contact with the ground or equatorial positions; however, it was improved when based on the stylar end of the fruit.


2008 ◽  
Vol 18 (3) ◽  
pp. 410-416 ◽  
Author(s):  
Stephen R. Delwiche ◽  
Weena Mekwatanakarn ◽  
Chien Y. Wang

A rapid, reliable, and nondestructive method for quality evaluation of mango (Magnifera indica) fruit is important to the mango industry for international trade. The objective of this study was to determine the potential of near-infrared (NIR) spectroscopy to predict soluble solids content (SSC) and individual and combined concentrations of sucrose, glucose, and fructose nondestructively in mango. Mature mangoes at two different temperatures (15 °C and 20 °C) were measured by NIR interactance (750–1088 nm wavelength region analyzed) over an 11-day period, starting when the fruit were underripe and extending to a few days past optimal ripeness. Partial least squares regression was used to develop models for SSC, individual sugar concentration, and the sum of the concentrations of the three sugars. Such analyses yielded calibration equations with R2 = 0.77 to 0.88 (SSC), 0.75 (sucrose), 0.67 (glucose), 0.70 (fructose), and 0.82 (sum); standard error of calibration = 0.56 to 0.90 (SSC), 10.0 (sucrose), 0.9 (glucose), 4.5 (fructose), and 10.4 (sum); and standard error of cross-validation = 0.93 to 1.10 (SSC), 15.6 (sucrose), 1.4 (glucose), 6.9 (fructose), and 16.8 (sum). When the SSC calibration was applied to a separate validation set, the standard error of performance ranged from 0.94% to 1.72%. These results suggest that for assessment of mango ripeness, NIR SSC calibrations are superior to the NIR calibrations for any of the individual sugars. This nondestructive technology can be used in the screening and grading of mangoes and in quality evaluation at wholesale and retail levels.


2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Charles L. Y. Amuah ◽  
Ernest Teye ◽  
Francis Padi Lamptey ◽  
Kwasi Nyandey ◽  
Jerry Opoku-Ansah ◽  
...  

The potential of predicting maturity using total soluble solids (TSS) and identifying organic from inorganic pineapple fruits based on near-infrared (NIR) spectra fingerprints would be beneficial to farmers and consumers alike. In this study, a portable NIR spectrometer and chemometric techniques were combined to simultaneously identify organically produced pineapple fruits from conventionally produced ones (thus organic and inorganic) and also predict total soluble solids. A total of 90 intact pineapple fruits were scanned with the NIR spectrometer while a digital refractometer was used to measure TSS from extracted pineapple juice. After attempting several preprocessing techniques, multivariate calibration models were built using principal component analysis (PCA), K-nearest neighbor (KNN), and linear discriminant analysis (LDA) to identify the classes (organic and conventional pineapple fruits) while partial least squares regression (PLSR) method was used to determine TSS of the fruits. Among the identification techniques, the MSC-PCA-LDA model accurately identified organic from conventionally produced fruits at 100% identification rate. For quantification of TSS, the MSC-PLSR model gave Rp = 0.851 and RMSEC = 0.950 °Brix, and Rc = 0.854 and RMSEP = 0.842 °Brix at 5 principal components in the calibration set and prediction set, respectively. The results generally indicated that portable NIR spectrometer coupled with the appropriate chemometric tools could be employed for rapid nondestructive examination of pineapple quality and also to detect pineapple fraud due to mislabeling of conventionally produced fruits as organic ones. This would be helpful to farmers, consumers, and quality control officers.


Holzforschung ◽  
2008 ◽  
Vol 62 (4) ◽  
Author(s):  
Kyösti Karttunen ◽  
Asta Leinonen ◽  
Matti-Paavo Sarén

Abstract Moisture content distributions of Scots pine logs in the green state were measured by a novel multi-step procedure. After sample preparation, the transverse sections of the wood surfaces were scanned by an automated scanning device with a fiber optical probe connected to a Fourier transform near-infrared spectroscope. In the course of the measurement sequences, several issues were addressed, such as surface drying, measurement geometry, ease of automation and interconnected data handling. The near-infrared (NIR) data were first modeled separately for heartwood and sapwood by means of multivariate partial least squares regression. The models for moisture content were evaluated by root mean square error of prediction, the result being 0.8% for heartwood and 10% for sapwood. The two models were then applied to the NIR data collected from sets of disks cut from nine logs. The results of the calculated moisture contents were evaluated by methods of descriptive statistics, and they indicated clear differences and trends in the distribution of moisture content in transverse or longitudinal regions of a log. Additionally, inter-tree variation in moisture content was detected.


Holzforschung ◽  
2011 ◽  
Vol 65 (5) ◽  
Author(s):  
Vimal Kothiyal ◽  
Aasheesh Raturi

Abstract Near infrared spectroscopy coupled with multivariate data analysis has been used to predict the specific gravity, modulus of rupture, modulus of elasticity, and fiber stress at elastic limit in bending tests on radial and tangential strip wood samples obtained from five-year-old Eucalyptus tereticornis. Moisture content of samples was 6–21% for bending test and 7–16% for specific gravity. Partial least squares regression calibrations were developed for each wood property. Calibrations had good relationships between values measured in laboratory and NIR predicted values obtained from small clear samples. The coefficient of determination (R2) for calibration ranged from 0.76 to 0.83 and for prediction (Rp 2) it was between 0.58 and 0.77. Both radial and tangential faces are equally suited for calibration (for radial face R2 was 0.77–0.83 and for tangential it was 0.76–0.83). Standard errors of predictions were slightly higher compared to standard error of calibration.


2021 ◽  
Vol 1208 (1) ◽  
pp. 012022
Author(s):  
Nebojša Todorović

Abstract Fourier transform near-infrared (FT-NIR) spectroscopy and partial least squares regression (PLS-R) were tested for the possibility of equilibrium moisture content (EMC) prediction in thermally modified beech wood (Fagus moesiaca C.). The samples were modified for 4h at temperatures of 170, 190 and 210 °C. After thermal modification, the samples were kept in a climatic chamber until EMC was reached. FT-NIR spectra (100 scans and 4 cm-1) were collected on the cross-section and radial surfaces at four points. PLS – R models were developed for four spectral regions: the first overtone, the second overtone, the third overtone and the combination band region. Applied thermal treatment caused a decrease of EMC by 42 % at 170 °C, by 53 % at 190 °C, and by 62 % at 210 °C. Principal component analysis (PCA) indicated that there is a difference both between treatments and between wood surfaces. The results of the spectra taken from the radial surface were, in all models, better than the spectra of the cross-section. Related to chemical changes, the first and second overtone region play an important role in the calibrations. The best prediction models for EMC of thermally modified beech wood were obtained from radial surface spectra in the first (Rp2=0.86, RPD=2.69) and second overtone region (Rp2=0.87, RPD=2.70). The obtain results could contribute to the development of predictive models in monitoring of EMC which could significantly improve the quality of industrial production of thermally modified wood.


Author(s):  
Huseyin Ayvaz

The objective of this study was to develop a rapid infrared technique to determine 10 key quality parameters (sucrose, glucose, fructose, reducing sugar, 5-HMF, °Brix, moisture content, water activity, pH and free acidity) in honey by using new generation portable and handheld devices. The composition of honey samples (n=59) collected from different parts of Turkey was analyzed by using established reference methods, giving wide range of concentrations for each parameter. The levels of sucrose and 5-HMF in some samples were above the established regulatory limits (Codex Alimentarius and European Union standards), indicating possible adulteration or process and storage abuse. Spectra were collected by using portable Fourier-Transformed infrared (FTIR) and handheld NIR (Near Infrared) spectrometers. Partial least squares regression (PLSR) approach was used to correlate the spectral features with compositional reference values, giving strong linear correlation coefficients and standard errors of prediction. Although both systems performed similarly, portable FTIR system was superior in predictions of sucrose, 5-HMF and free acidity while portable NIR system performed noticeably better for °Brix and moisture content. The data indicates that all of the 10 parameters can be measured within the minutes using both systems, providing reliable screening capabilities, flexibility and the potential for in-field applications.


2021 ◽  
Vol 13 (19) ◽  
pp. 10747
Author(s):  
Khadija Najjar ◽  
Nawaf Abu-Khalaf

The non-destructive visible/near-infrared (VIS/NIR) spectroscopy is a promising technique in determining the quality of agricultural commodities. Therefore, this study aimed to examine the ability of VIS/NIR spectroscopy (550–1100 nm) to distinguish between three different varieties of tomato (i.e., Ekram, Harver and Izmer), as well as to predict the quality parameters of tomato, such as soluble solids content (SSC), titratable acidity (TA), taste (SSC/TA) and firmness. Ninety intact samples from three tomato varieties were used. These samples were examined using VIS/NIR spectroscopy and quality parameters were also measured using traditional methods. Principal component analysis (PCA) and partial least square (PLS) were carried out. The results of PCA showed the ability of VIS/NIR spectroscopy to distinguish between the three varieties, where two PCs explained about 99% of the total variance in both calibration and validation sets. Moreover, PLS showed the possibility of modelling quality parameters. The correlation coefficient (R2) and the ratio of performance deviation (RPD) for all quality parameters (except for firmness) were found to be higher than 0.85 and 2.5, respectively. Thus, these results indicate that the VIS/NIR spectroscopy can be used to discriminate between different varieties of tomato and predict their quality parameters.


Holzforschung ◽  
2015 ◽  
Vol 69 (3) ◽  
pp. 329-335 ◽  
Author(s):  
Hikaru Kobori ◽  
Tetsuya Inagaki ◽  
Takaaki Fujimoto ◽  
Tsutomu Okura ◽  
Satoru Tsuchikawa

Abstract A fast online grading apparatus for sawn lumber based on near-infrared (NIR) spectroscopy has been developed. The method is based on a novel wavelength dispersive NIR spectrophotometer equipped with a diffraction grating linear sensor and high-intensity lighting. It was possible to acquire spectra from the entire surface of Hinoki cypress lumber sections traveling on a conveyor belt at a speed of 120 m min-1. Additionally, predictive models for moisture content (MC) and modulus of elasticity (MOE) under various MC conditions were developed from the NIR spectra with the aid of partial least squares regression (PLSR) analysis. Both the MC and MOE predictive models demonstrated sufficient levels of prediction accuracy for use on high-speed conveyor belts, and the results of various experiments indicate that the developed device could be applied for the online quality certification of sawn lumber in commercial sawmills.


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