Quantification of Total Phenolic and Carotenoid Content in Blackberries (Rubus Fructicosus L.) Using Near Infrared Spectroscopy (NIRS) and Multivariate Analysis

Abstract

A rapid method to quantify the total phenolic content (TPC) and total carotenoid content (TCC) in blackberries using near infrared spectroscopy (NIRS) was carried out aiming to provide reductions in analysis time and cost for the food industry. A total of 106 samples were analysed using the Folin-Ciocalteu method for TPC and a method based on Ultraviolet-Visible Spectrometer for TCC. The average contents found for TPC and TCC were 24.27 mg·g−1 dw and 8.30 µg·g−1 dw, respectively. Modified partial least squares (MPLS) regression was used for obtaining the calibration models of these compounds. The RPD (ratio of the standard deviation of the reference data to the standard error of prediction (SEP)) values from external validation for both TPC and TCC were between 1.5 < RPDp < 2.5 and RER values (ratio of the range in the reference data to SEP) were 5.92 for TPC and 8.63 for TCC. These values showed that both equations were suitable for screening purposes. MPLS loading plots showed a high contribution of sugars, chlorophyll, lipids and cellulose in the modelling of prediction equations.

Investigation on High-Value Bioactive Compounds and Antioxidant Properties of Blackberries and Their Fractions Obtained by Home-Scale Juice Processing

“…Prior to the extraction procedure, the blackberries and raw byproducts were crushed, while the dried byproduct samples were grinded with a laboratory mill, Grindomix GM200 (Retsch, Haan, Germany), until a powder granulation was obtained [29]. The size reduction in the solute led to a better mass transfer produced by the increased affinity between solute and solvent, resulting in an effective bioactive compound extraction [30,31]. The ethanol/water mixture (1:1, v/v) was used as the extraction solvent and the solid:solvent extraction ratio was 1:10 (w/v).…”

Detection of the BRAF V600E Mutation in Colorectal Cancer by NIR Spectroscopy in Conjunction with Counter Propagation Artificial Neural Network

“…That is, the NIR absorption bands are seriously overlapping, so that NIR spectra are not directly interpreted and utilized. Thence, it is necessary to extract the information on the analytes from the NIR data for the sample by chemometric techniques [11,12,13]. NIR spectroscopy, assisted by chemometric techniques, is used to discriminate cancer from benign tumor, such as breast cancer [14], endometrial cancer [15], gastric cancer [16], and colorectal cancer [17], because it is easy-to-use, robust, inherently rapid (measuring a NIR spectrum in seconds), as well as nondestructive and low-cost [18,19].…”

Quantification of Water, Protein and Soluble Sugar in Mulberry Leaves Using a Handheld Near-Infrared Spectrometer and Multivariate Analysis

“…NIR spectroscopy is widely used in food for advantages rapid detection, low analysis cost, excellent reproducibility [9][10][11]. Toledo-Martín et al [12] used NIR spectroscopy and modified partial least squares (MPLS) to establish a regression model for the fast determination of total phenolic content (TPC) and total carotenoid content (TCC) in blackberry. The ratio of the standard deviation to standard error of prediction (performance) (RPD) and ratio of the range to standard error of prediction (RER) of the TPC model were 1.52 and 5.92, respectively, and the RPD and RER of the TCC model were 1.82 and 8.63, respectively.…”