Prediction of sensory texture quality attributes of cooked potatoes by NMR-imaging (MRI) of raw potatoes in combination with different image analysis methods

Effect of boiling on classification performance of potatoes determined by computer vision

The aim of this study was to evaluate the effect of potato boiling on the correctness of cultivar discrimination. The research was performed in an objective, inexpensive and fast manner using the image analysis technique. The textures of the outer surface of slice images of raw and boiled potatoes were calculated. The discriminative models based on a set of textures selected from all color channels (R, G, B, L, a, b, X, Y, Z, U, V, S), textures selected for color spaces and textures selected for individual color channels were developed. In the case of discriminant analysis of raw potatoes of cultivars ‘Colomba’, ‘Irga’ and ‘Riviera’, the accuracies reached 94.33% for the model built based on a set of textures selected from all color channels, 94% for Lab and XYZ color spaces, 92% for color channel b and 92.33% for a set of combined textures selected from channels B, b, and Z. The processed potatoes were characterized by the accuracy of up to 98.67% for the model including the textures selected from all color channels, 98% for RGB color space, 95.33% for color channel b, 96.67% for the model combining the textures selected from channels B, b, and Z. In the case of raw and processed potatoes, the cultivar ‘Irga’ differed in 100% from other potato cultivars. The results revealed an increase in cultivar discrimination accuracy after the processing of potatoes. The textural features of the outer surface of slice images have proved useful for cultivar discrimination of raw and processed potatoes.

Prediction of residual film perception of cosmetic products using an instrumental method and non-biological surfaces: The example of stickiness after skin application

Prediction of sensory texture attributes using instrumental measurements is a very important challenge for cosmetic industry because in vivo sensory studies are expensive, time consuming and limited by the safety issue of applied products. The aim of this work is to investigate how residual sensory properties of cosmetic products can be predicted without using a panel of assessors, focusing on the residual film attribute "Stickiness". 10 cosmetic products with different galenics have been selected and evaluated in vivo using a classical sensory protocol, developed according to the Spectrum^™ Descriptive Analysis method. In addition to this study, products were evaluated after their application on non-biological skin models in order to compare perceptions onto in vivo skin and artificial surfaces. Results obtained show that in vivo perceptions can be compared with the ones on artificial surfaces meaning that residual film stickiness is similar between in vivo skin and non-biological skin models. An instrumental protocol using a texture analyzer has been set up to evaluate residual film adhesiveness. This protocol has been tested and validated in vivo (r²_adjusted = 0.90; RPD = 3.07) before being optimized on a selected non-biological skin model Bioskin® (Beaulax, Co. Ltd. Tokyo, Japan) owning good correlation with in vivo perceptions. Established model shows excellent predictive ability with a r²_adjusted of 0.94 and a RPD of 3.38, as highlighted by the 4 steps cross-validation performed. It proves that physical stimulus responsible for cosmetic film stickiness can be instrumentally measured on both in vivo skin and artificial skin.

Use of Magnetic Resonance Imaging in Food Quality Control: A Review

Modern challenges of food science require a new understanding of the determinants of food quality and safety. Application of advanced imaging modalities such as magnetic resonance imaging (MRI) has seen impressive successes and fast growth over the past decade. Since MRI does not have any harmful ionizing radiation, it can be considered as a magnificent tool for the quality control of food products. MRI allows the structure of foods to be imaged noninvasively and nondestructively. Magnetic resonance images can present information about several processes and material properties in foods. This review will provide an overview of the most prominent applications of MRI in food research.

Effects of Fish-Derived Biological Preservatives on Cold Storage of Grass Carp ( Ctenopharyngodon idellus ) Fillets

Two kinds of fish-derived natural antimicrobial substances, protamine and catfish ( Clarias fuscus ) epidermal mucus extract (CEME), were evaluated for their effect on the quality of grass carp fillets. Fillets were atmosphere packaged in cast polypropylene bags and were stored at 4°C in a low-temperature incubator without light. Solutions (0.5%, wt/vol) of CEME and protamine were used for dip pretreatment, respectively. Bacteriological (aerobic plate count, Shewanella putrefaciens , Pseudomonas fluorescens ) and physicochemical (pH, total volatile basic nitrogen, K value, surface color, texture profiles, water distribution) parameters and volatile odor compounds were measured on days 0, 3, 6, 9, 12, and 15. The results indicated that CEME and protamine could improve all bacteriological and physicochemical indexes, except water distribution within muscle. In comparison, CEME had a more inhibitory effect, as determined by the aerobic plate count, and was more effective in inhibiting the growth of P. fluorescens ; however, protamine was more effective in preventing the production of sulfur-organic (H₂S) group substances. Protamine was more effective in inhibiting the growth of S. putrefaciens . This research suggests that protamine and CEME have the potential to improve the quality and extend the shelf life of grass carp fillets.

A comparison of the eating quality of selected potato cultivars from two potato production regions in South Africa

BACKGROUND

Limited scientific information is available on the eating quality of potato cultivars in South Africa. This study aimed to determine, describe and compare the eating quality of three potato cultivars from two production regions (dry land and irrigated land) in South Africa, through sensory and physical evaluation. Sensory descriptors were identified for the sensory attributes and a lexicon was developed. A category scale was used to rate the sensory attributes and physical measurements of specific gravity, shear force resistance and scanning electron microscopy were performed.

RESULTS

It became evident that both sensory evaluation and physical measurements need to be performed in order to determine the eating quality of potato cultivars, as one evaluation supports the other. A partial least squares regression modelling method was used to relate the sensory attributes and physical measurements. The intensity of the sensory attributes of the specific cultivars varied between the two production regions.

CONCLUSION

The eating quality of potatoes obtained from two production regions differed from another due to climatic conditions and other production characteristics that exist (dry land vs. irrigation). The study confirms the valuable contribution of determining the eating quality of potato cultivars.

Comparison of gas chromatography-coupled time-of-flight mass spectrometry and 1H nuclear magnetic resonance spectroscopy metabolite identification in white wines from a sensory study investigating wine body

Metabolite profiles of white wines, including Chardonnay, Pinot gris, Riesling, Sauvignon blanc, and Viognier varieties, were determined using both gas chromatography-coupled time-of-flight mass spectrometry (GC-TOF-MS) and proton nuclear magnetic resonance spectroscopy ((1)H NMR). A total of 108 metabolites were identified by GC-TOF-MS, and 51 metabolites were identified by (1)H NMR; the majority of metabolites identified include the most abundant compounds found in wine (ethanol, glycerol, sugars, organic acids, and amino acids). Compositional differences in these wines correlating to the wine sensory property "body", or viscous mouthfeel, as scored by a trained panel were identified using partial least-squares (PLS) regression. Independently calculated GC-TOF-MS and NMR-based PLS models demonstrate potential for predictive models to replace expensive, time-consuming sensory panels. At the modeling stage, correlations between the measured and predicted values have coefficients of determination of 0.83 and 0.75 for GC-TOF-MS and (1)H NMR, respectively. Additionally, the MS- and NMR-based models present new insights into the chemical basis for wine mouthfeel properties.

MaZda--a software package for image texture analysis

MaZda, a software package for 2D and 3D image texture analysis is presented. It provides a complete path for quantitative analysis of image textures, including computation of texture features, procedures for feature selection and extraction, algorithms for data classification, various data visualization and image segmentation tools. Initially, MaZda was aimed at analysis of magnetic resonance image textures. However, it revealed its effectiveness in analysis of other types of textured images, including X-ray and camera images. The software was utilized by numerous researchers in diverse applications. It was proven to be an efficient and reliable tool for quantitative image analysis, even in more accurate and objective medical diagnosis. MaZda was also successfully used in food industry to assess food product quality. MaZda can be downloaded for public use from the Institute of Electronics, Technical University of Lodz webpage.