Piotr Zapotoczny

Effect of Variety on Drying Characteristics and Selected Quality Attributes of Dried Carrots

The effects of variety on drying characteristics, color, and water absorption of carrots were investigated. Six different varieties of carrots, viz. Kazan, Maxima, Nandor, Nektarina, Simba, and Tito were evaluated. The hot air drying characteristics of carrot cubes dried under forced convection conditions were determined and drying data were analyzed to obtain parameters of Page and first-order kinetic models as well as moisture diffusivity. Color characteristics were determined for fresh, dried, and dehydrated samples by measuring lightness (L*), redness (a*), and yellowness (b*). Water absorption data were analyzed for ground samples. It was observed that drying characteristics, such as color and water absorption were significantly influenced by variety. The varieties of Kazan and Nektarina were found to be characterized by highest and lowest moisture diffusivity of 7.52 × 10−9 and 3.31 × 10−9m2/s respectively. Kazan variety was also characterized by shortest drying time. The lowest changes in color caused by drying were observed for Tito variety. The variety of Kazan was characterized by the highest resistances to color changes affected by drying followed by rehydration. Nandor and Tito varieties displayed the highest water absorption near to 560 g/100 g. The best drying characteristics and good water absorption accompanied by the high color attributes of dried and rehydrated samples implies that Kazan variety is expected to be the most useful to drying industry.

Identifying barley varieties by computer vision

Abstract Visual discrimination between barley varieties is difficult, and it requires training and experience. The development of automatic methods based on computer vision could have positive implications for the food processing industry. In the brewing industry, varietal uniformity is crucial for the production of high quality malt. The varietal purity of thousands of tons of grain has to be inspected upon purchase in the malt house. This paper evaluates the effectiveness of identification of barley varieties based on image-derived shape, color and texture attributes of individual kernels. Varieties can be determined by means of discriminant analysis, including reduction of feature space dimensionality, linear classifier ensembles and artificial neural networks, with high balanced accuracy ranging from 67% to 86%. The study demonstrated that classification results can be significantly improved by standardizing individual kernel images in terms of their anteroposterior and dorsoventral orientation and performing additional analyses of wrinkled regions.

Microwave Vacuum–Assisted Drying of Green Peas Using Heat Pump and Fluidized Bed: A Comparative Study Between Atmospheric Freeze Drying and Hot Air Convective Drying

This study investigates the performance of microwave vacuum–assisted drying (MVD) of green peas using both fluidized bed and heat pump systems. A comparative study of heat pump–fluidized bed atmospheric freeze drying (HP-FB-AFD) and heat pump–fluidized bed hot air convective drying (HP-FB-HACD) was conducted. The initial drying rates of green peas were 0.04 and 0.12 1/min for HP-FB-AFD and HP-FB-HACD, respectively. Moisture diffusivity of green peas dried in HP-FB-HACD and HP-FB-AFD were 1.04 × 10−9 and 6.94 × 10−11 m2/s, respectively. HP-FB-AFD did not entail changes in the starch granules and preserved the sample size and shape with minimal shrinkage (20%), whereas HP-FB-HACD generated significant volumetric shrinkage (50%). HP-FB-AFD+MVD created a desirable porous inner structure of the final product. HP-FB-HACD+MVD significantly increased the hardness of the dried product and produced green peas with a compact structure and tightly packed cells. Neither HP-FB-AFD+MVD nor HP-FB-HACD+MVD significantly influenced the color of dried green peas. To respond to the current demand for high-quality products, the multistage combined HP-FB-AFD+MVD method is an interesting technique for green peas processing.

Rheological Behavior of Hot-Air-Puffed Amaranth Seeds

Force-deformation and force-relaxation experiments were performed on amaranth seeds puffed at 290, 330 and 370°C. Less force and energy was required to cause a given deformation in seeds processed at 290°C than in those puffed at 330 and 370°C. It was also observed that the forces and energies required to produce a given deformation did not differ significantly (p ≤ 0.05) for seeds puffed at 330 and 370°C. The three-element generalized Maxwell model and Peleg model were applied for modeling force relaxation of puffed amaranth seeds. It was found that the generalized Maxwell model predicted the experimental data better than the Peleg model. The elastic parameters and asymptotic residual force of the generalized Maxwell model were significantly affected by puffing temperature, showing an increase with its rise. Relaxation times were not significantly affected by the puffing temperature. It was concluded that a higher puffing temperature resulted in a more rigid material and less viscous behavior.

Discrimination of Wheat Grain Varieties Using Image Analysis and Multidimensional Analysis Texture of Grain Mass

This article presents the results of discrimination of 11 wheat grain varieties. The statistical analysis included reduction of variables to a set of 49 textures with the highest discriminating strength and multidimensional analysis. Reduction of variables was performed by the following methods: genetic algorithms (sequential forward floating search [SFFS] method) as well as the Class Ranker and Class RankersSearch methods. Furthermore, the multidimensional analysis was performed by methods employing the following classifiers: Bayes, Lazy, Meta, Decision trees, and Discriminatory analyses. The classification of individual varieties, regardless of the year of cultivation, was between 98 and 100%.

A Comparative Analysis of Colour Measurements of the Seed Coat and Endosperm of Wheat Kernels Performed by Various Techniques

The results of this present studies show that the colour of the seed coat of wheat kernels can be determined by digital image analysis (DIA) instead of spectrophotometry. High linear correlations (p < 0.05) were found between colour measurements of the seed coat performed by these techniques. The colour on the cross-sections of wheat kernels was related to the colour of their seed coat. A high correlation was also observed between the colour of the seed coat and the colour of the endosperm of wheat kernels. In all measurements colour was described by the RGB, XYZ, and L*a*b* models. Colour indices, i.e. hue (h0) and saturation (S*) were also calculated.

Application of Hyperspectral Imaging for Cultivar Discrimination of Malting Barley Grains

Abstract The aim of this study was to perform and evaluate the accuracy of classification of grains of different cultivars of malting barley. The grains of eight cultivars: Blask, Bor do, Con chita, Kormoran, Mercada, Serwal, Signora, Victoriana, with three moisture content: 12, 14, 16% were examined. The selected parameters of the surface texture of grain mass obtained from images taken using the techniques of hyperspectral imaging were determined. The accuracy of grains discrimination carried out using different methods of selection and classification of data was compared. The pairwise comparison and comparison of three, four and eight cultivars of malting barley were carried out. The most accurate discrimination was determined in the case of the pairwise comparison. Victoriana cultivar was the most different from the others. The most similar texture of grain mass was found in the comparison of cultivars: Blask and Mercada. In the case of eight examined cultivars of malting barley, the most accurate discrimination (classification error – 55%) was obtained for images taken at the moisture content of 14% and at a wavelength of 750 nm, for the attributes selection performed with the use of probability of error and average correlation coefficient (POE+ACC) method and the discrimination carried out using the linear discriminant analysis (LDA).

The use of computer-assisted image analysis in the evaluation of the effect of management systems on changes in the color, chemical composition and texture of m. longissimus dorsi in pigs

The effect of management systems on selected physical properties and chemical composition of m. longissimus dorsi was studied in pigs. Muscle texture parameters were determined by computer-assisted image analysis, and the color of muscle samples was evaluated using a spectrophotometer. Highly significant correlations were observed between chemical composition and selected texture variables in the analyzed images. Chemical composition was not correlated with color or spectral distribution. Subject to the applied classification methods and groups of variables included in the classification model, the experimental groups were identified correctly in 35-95%. No significant differences in the chemical composition of m. longissimus dorsi were observed between experimental groups. Significant differences were noted in color lightness (L*) and redness (a*).

Species Composition and Trichothecene Genotype Profiling of Fusarium Field Isolates Recovered from Wheat in Poland

Fusarium head blight (FHB) of cereals is the major head disease negatively affecting grain production worldwide. In 2016 and 2017, serious outbreaks of FHB occurred in wheat crops in Poland. In this study, we characterized the diversity of Fusaria responsible for these epidemics using TaqMan assays. From a panel of 463 field isolates collected from wheat, four Fusarium species were identified. The predominant species were F. graminearum s.s. (81%) and, to a lesser extent, F. avenaceum (15%). The emergence of the 15ADON genotype was found ranging from 83% to 87% of the total trichothecene genotypes isolated in 2016 and 2017, respectively. Our results indicate two dramatic shifts within fungal field populations in Poland. The first shift is associated with the displacement of F. culmorum by F. graminearum s.s. The second shift resulted from a loss of nivalenol genotypes. We suggest that an emerging prevalence of F. graminearum s.s. may be linked to boosted maize production, which has increased substantially over the last decade in Poland. To detect variation within Tri core clusters, we compared sequence data from randomly selected field isolates with a panel of strains from geographically diverse origins. We found that the newly emerged 15ADON genotypes do not exhibit a specific pattern of polymorphism enabling their clear differentiation from the other European strains.

Classification of Fusarium-infected and healthy wheat kernels based on features from hyperspectral images and flatbed scanner images: a comparative analysis

Wheat infections caused by fungi of the genus Fusarium decrease yields and have serious economic consequences. The produced mycotoxins have harmful effects on human and animal health. The aim of this study was to develop classification models based on selected textural parameters to distinguish between infected and healthy wheat kernels. The classification accuracy of kernels positioned on the ventral side was determined at 78–100% in the model based on textural parameters from hyperspectral images, and at 95–100% based on images generated by a flatbed scanner. Kernels positioned on the dorsal side were correctly classified in 78–98% based on hyperspectral images, and in 92–100% based on colour images. In the models combining textural parameters from the ventral and dorsal sides of wheat kernels, classification accuracy reached 76–98% in hyperspectral images, and 94–100% in images generated by a flatbed scanner. The imaging technique—flatbed scanner and the ventral side of the kernels provided higher classification accuracy results. The results will contribute to further research aiming to develop models for the determination of fungal chemotypes and/or fungal species based on selected textural features of wheat kernels.