Evaluation of quality and nutraceutical content of blueberries (Vaccinium corymbosum L.) by near and mid-infrared spectroscopy

Sinelli, N.; Spinardi, A.; Egidio, Valentina Di; Mignani, I.; Casiraghi, E.

doi:10.1016/j.postharvbio.2008.03.013

Cited by 210 publications

(138 citation statements)

References 22 publications

Supporting

Mentioning

129

Contrasting

Unclassified

Order By: Relevance

“…c diethyl ether extracts of gooseberries, blueberries, and cranberries from the top to the bottom seabuckthorn ranged from 22.83 to 131.88 g/kg and 3.51 to 13.13 g/kg, respectively, which corresponds with our results. A number of reviewed articles showed that the main bioactive compounds determining the nutritional quality of berries are polyphenols, anthocyanins, and flavonoids [2,4,[23][24][25][26][27][28]. The high anthocyanin content and biological activities of these fruits indicate that their consumption would be beneficial to health.…”

Section: Discussionmentioning

confidence: 99%

“…The presence of polyphenols in the investigated berries samples was studied by Fourier transform infrared (FT-IR) spectroscopy. A Nicolet iS 10 FT-IR Spectrometer (Thermo Scientific Instruments LLC, Madison, WI, USA), with the smart iTR TM ATR (Attenuated Total Reflectance) accessory, was used to record IR spectra [23].…”

Section: Fluorometry and Fourier Transform Infrared (Ft-ir) Spectra Smentioning

confidence: 99%

See 1 more Smart Citation

Antioxidant activities and bioactive components in some berries

Namieśnik

Vearasilp

Kupska

et al. 2013

Eur Food Res Technol

View full text Add to dashboard Cite

The objective of this study was to evaluate the antioxidant and binding effects of gooseberry, a less-studied berry, and to compare with blueberry and cranberry in the model of interaction with human serum albumin (HSA). The relationship between the scavenging properties of dietary polyphenols of the selected berries and their affinities for HSA were investigated by fluorescence analysis. In order to perform the extraction and identification of the antioxidants present in the samples, different types of extraction solvents were used, such as water, ethyl acetate, and diethyl ether. The polyphenols, tannins, anthocyanins and ascorbic acid contents, and the total antioxidant capacities (TACs) of the berry extracts were assessed by using ESI-MS, FTIR, and radical scavenging assays. The contents of bioactive compounds and the levels of TACs in water extracts differed significantly and were the highest in water extracts in comparison with other extracts in all the investigated berries (P \ 0.05). Gooseberry water extracts contained: polyphenols (mg GAE/g DW)-5.37 ± 0.6, tannins (mg CE/g DW)-0.71 ± 0.2, anthocyanins (mg CGE/g DW)-12.0 ± 1.2, ascorbic acid (mg AA/g DW)-5.15 ± 0.5, and TACs (lMTE/g DW) by ABTS and FRAP assays were 15.53 ± 1.6 and 6.51 ± 0.7, respectively. In conclusion, the bioactivity of gooseberry was lower than blueberries and cranberries. The antioxidant and binding properties of gooseberries in comparison with widely consumed blueberries and cranberries can be used as a new source for food supplementation.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Fluorometry and Fourier Transform Infrared (Ft-ir) Spectra Smentioning

confidence: 99%

Antioxidant activities and bioactive components in some berries

Namieśnik

Vearasilp

Kupska

et al. 2013

Eur Food Res Technol

View full text Add to dashboard Cite

show abstract

“…The determination of the reliability and validity of a model which has already built can be seen from the value of the coefficient of correlation (r), the coefficient of determination (R 2 ), the root mean square errors (RMSE) at the time of calibration (RMSEC) and the ratio between the standard deviation with RMSEC (RPD). So, a good Model is if it has a high value of r, the smaller value of RMSEC than the standard deviation (SD) of the data and the high value of the RPD (Naes et al, 2004;Sinelli et al, 2008). The formula used to calculate RMSEC and RPD is as follows: Out of the two methods using pretreatment and without using any pretreatment were performed the comparison and the election method which was the best method to predict the content of heavy metals in soils of paddy fields and the fields.…”

Section: The Development Of Calibration Modelmentioning

confidence: 99%

The prediction of heavy metals lead (Pb) and zinc (Zn) contents in soil using NIRs technology and PLSR regression method

Husnizar

Wilopo

Yuliansyah

2018

J.Degrade.Min.Land Manage.

View full text Add to dashboard Cite

:The case of soil contamination by heavy metals in environment shows an increasing amount along with the constructions and development period that has been done. The identification of heavy metal content in the field is extremely hard to be done without a laboratory activity. Therefore, it needs a quick and non-destructive approach or method to identify the metal content of the soil in the field. The application of Near Infrared Reflectance Spectroscopy (NIRs) technology is a method that nondestructively able to detect the heavy metal content in the soil by using Partial Least Square Regression (PLSR). Pretreatment spectrum which is done using the Multiplicative Scatter Correction (MSC) can improve the results of the prediction models of PLSR. The results of MSC pretreatment spectrum can repair and improve the accuracy of the predictions of Lead (Pb) and Zinc (Zn) in the soil. Eight samples were used for analysis of each of Pb and Zn content. The measured data were pre-treated by MSC. It was obtained that value of r = 0.98, R 2 = 0.97 and RPD = 6.46 for the Pb content measurement. Meanwhile, the measurement for Zn obtained the value of r = 0.98, R 2 = 0.97 and RPD = 6.28. Therefore, it can be inferred that the NIRs is one of technologies which is worth reckoned as the right and quick means to predict the content of heavy metals in soil in a non-destructively and environmentally friendly way. Keywords: heavy metals, NIRs, PLSR, solid, standar solutionTo cite this article: Husnizar, Wilopo, W. and Yuliansyah, A.T. 2018. The prediction of heavy metals lead (Pb) and zinc (Zn) contents in soil using NIRs technology and PLSR regression method.

show abstract

“…Blueberries are highly perishable and the final quality of berries depends on their cultivars (Faria et al 2005;Sinelli et al 2008;Eum et al 2013). A blueberry cultivar is suitable for growing in Estonia when it is able to tolerate northern climatic conditions, for example it must be winter hardy (Albert et al 2010).…”

Section: Blueberry Post-harvest Factorsmentioning

confidence: 99%

Non-stationary processing centre for small and mediumsized blueberry farms. A Review

Soots¹,

Olt²

2017

Res. Agric. Eng.

View full text Add to dashboard Cite

Soots K., Olt J. (2017): Non-stationary processing centre for small and medium-sized blueberry farms. A Review. Res. Agr. Eng., 63: 136-144.Growing blueberries on exhausted milled peat fields could be a possible solution to decrease carbon dioxide emission from these areas. To operate such crop-giving plantation manually, a lot of manpower is needed. To decrease the manpower, suitable and helpful technical solutions should be introduced. The aim of this article is to investigate different technological aspects of post-harvest processing of blueberries and to study already existing technical solutions. As a result, non-stationary processing centre for small or medium-sized blueberry farms is proposed. The proposed solution allows reducing manpower, lowering production costs and increasing the area used for growing blueberries. Also, it may encourage other farms to start growing blueberries.

show abstract

Evaluation of quality and nutraceutical content of blueberries (Vaccinium corymbosum L.) by near and mid-infrared spectroscopy

Cited by 210 publications

References 22 publications

Antioxidant activities and bioactive components in some berries

Antioxidant activities and bioactive components in some berries

The prediction of heavy metals lead (Pb) and zinc (Zn) contents in soil using NIRs technology and PLSR regression method

Non-stationary processing centre for small and mediumsized blueberry farms. A Review

Contact Info

Product

Resources

About