RELATIONSHIP BETWEEN INSTRUMENTAL AND SENSORY PARAMETERS OF COOKED SWEETPOTATO TEXTURE1

This study compared two instrumental methods, namely uniaxial compression and texture profile analysis (TPA), with sensory evaluation in describing the textural properties of cooked sweetpotatoes. The steamed cooked samples (1.35 × 2.2 cm cylinder) of four cultivars and six selections were subjected to a trained texture profile panel for sensory ratings and the two instrumental methods for determination of the mechanical properties. Factor analysis indicated that the 15 sensory variables were grouped into 3 main factors, namely moistness-firmness (factor 1), particles (factor 2), and fiber (factor 3). Among the instrumental parameters, shear stress of compression and fracturability, hardness, and gumminess of TPA correlated highly (R = 0.73–0.95) with both the mouthfeel and mechanical-type sensory notes. These parameters of the two instrumental methods were linearly related (R²≥ 0.95) and could be converted from one to another with a high degree of reliability. Regression equations based on shear stress significantly explained (R²= 0.71–0.91) eight of the sensory notes. These instrumental parameters can be good predictors of cooked sweetpotato texture.     

PHYSICOCHEMICAL PROPERTIES OF GLUTEN-FREE PANCAKES FROM RICE AND SWEET POTATO FLOURS

Gluten‐free pancakes were prepared using rice flour and rice flour replaced with various amounts, at 10, 20 and 40%, of sweet potato flour. Textural properties of the cooked pancakes, such as hardness and chewiness generally increased with time after cooking, whereas they decreased with increased sweet potato flour replacement. On the other hand, cohesiveness decreased with time, but increased with increased sweet potato flour in the pancake. Nutritional properties of the rice–sweet potato pancakes, such as protein content, dietary fiber, total carbohydrate and calories were generally comparable with those of their wheat counterpart. The only significant difference was in the beta‐carotene content, which increased from 5.2 to 236.1 μg/g when sweet potato flour was incorporated, from 0 to 40%, into the rice pancake formulation.     

QUANTITATIVE MEASUREMENT OF FOOD SPREADABILITY USING THE VANE METHOD

This study was performed to describe an application of the vane method for the rapid, quantitative measurement of spreadability, a subjective, textural property. Yield points of thirteen commercial food items were determined and related to spreadability using models HBTDV-I and 5X HBTDV-I Brookfield viscometers equipped with three different vanes. Spreadability strongly impacts consumer approval of a food. This textural property has been linked to the yield stress of a material, but observations support that strain at yielding may also be important. A textural map, showing yield stress and yield strain of the selected foods was created to chart regions of spreadability.     

A deep feed-forward neural network for damage detection in functionally graded carbon nanotube-reinforced composite plates using modal kinetic energy

This paper proposes a new Deep Feed-forward Neural Network (DFNN) approach for damage detection in functionally graded carbon nanotube-reinforced composite (FG-CNTRC) plates. In the proposed approach, the DFNN model is developed based on a data set containing 20 000 samples of damage scenarios, obtained via finite element (FE) simulation, of the FG-CNTRC plates. The elemental modal kinetic energy (MKE) values, calculated from natural frequencies and translational nodal displacements of the structures, are utilized as input of the DFNN model while the damage locations and corresponding severities are considered as output. The state-of-the art Exponential Linear Units (ELU) activation function and the Adamax algorithm are employed to train the DFNN model. Additionally, in order to enhance the performance of the DFNN model, the mini-batch and early-stopping techniques are applied to the training process. A trial-and-error procedure is implemented to determine suitable parameters of the network such as the number of hidden layers and the number of neurons in each layer. The accuracy and capability of the proposed DFNN model are illustrated through two distinct configurations of the CNT-fibers constituting the FG-CNTRC plates including uniform distribution (UD) and functionally graded-V distribution (FG-VD). Furthermore, the performance and stability of the DFNN model with the consideration of noise effects on the input data are also investigated. Obtained results indicate that the proposed DFNN model is able to give sufficiently accurate damage detection outcomes for the FG-CNTRC plates for both cases of noise-free and noise-influenced data.     

Study of MEH–PPV/PCBM active layer morphology and its application for hybrid solar cell performance

Surface morphologies of MEH?CPPV:PCBM active layers were optimized by investigating ITO substrate treated with oxygen and nitrogen plasma. This treatment effectively improved smoothness, transmittance, and contact angle of ITO??s, resulting in good anode contacts for hybrid device structures. The consistently improved performance of hybrid solar cells was also achieved. The surface properties of treated and untreated ITO substrates were compared by contact angle, four point probe, scanning electron microscopy, and atomic force microscopy.     

Textural Properties and Sensory Quality of Processed Sweetpotatoes as Affected by Low Temperature Blanching

Sweetpotatoes (SP) stored for 9–12 mo after harvest were cut into cylindrical pieces and, following factorial experiments and response surface design, were blanched at 50–80°C for 15–274 min. Instrumental textural properties were measured by uniaxial compression and texture profile analysis. Samples of selected blanching treatments were canned in syrup for textural and sensory evaluations. Both blanching temperature and time had significant effects on firmness. Optimal temperature for maximal firmness retention was about 62°C. For canned SP, the 62°C blanched samples were more intact (2–3-fold) and firmer (2–7-fold) than controls. Sensory texture and overall acceptability were greatest for samples blanched at 62°C for 30 or 45 min before canning.     

ALKALI-NEUTRALIZATION PROCESS MAINTAINS THE FIRMNESS AND SENSORY QUALITY OF CANNED SWEETPOTATO PIECES1

Jewel cultivar SP stored 1, 5, and 10 months after harvest were peeled, cut into pieces, treated, and canned in 15 and 30 deg Brix syrups. Samples were evaluated for degree of disintegration (wholeness), firmness (shear force), chemical composition, and sensory acceptance. Untreated samples (controls) disintegrated as storage time prior to processing increased, while treated samples remained intact; firmness and sensory texture scores declined with increasing storage time. Treated samples were significantly firmer than controls throughout the study, and, although shear force declined over time, sensory panelists did not detect any texture change. Overall sensory acceptance at 10 months was greatest for phosphate-treated samples in 30 deg Brix syrup. Thus, the alkali-neutralization process retains firmness, wholeness, and sensory quality of SP canned after long-term storage. This process will permit commercial processing of SP roots stored for up to 10 months.     

COMPARATIVE STUDY OF LARGE STRAIN METHODS FOR ASSESSING FAILURE CHARACTERISTICS OF SELECTED FOOD GELS

Vane rheometry was compared with uniaxial compression and torsion in evaluating the effects of strain rate on failure shear stress and deformation of soybean protein (tofu) and gellan gum gels. A Haake VT 550 viscotester was used for torsion and vane tests, and compression was performed with an Instron/MTS universal testing machine. Strain or angular deformation at failure was independent of strain rate in the three testing modes. In vane rheometry, failure shear stress increased with increasing low shear rates (< 0.100 s ⁻¹) and was rate independent at higher rates. This strain rate dependency was also evident in compression, varying with the material. For torsion, fracture stress appeared to be rate independent. Shear fracture stresses measured in torsion and compression were in good agreement at strain rates above 0.025 s ⁻¹ and 0.100 s ⁻¹ for tofu and gellan gels, respectively. Shear stresses from the vane method were lower than shear stresses of torsion and compression. Similar texture maps of the food gels studied were generated by plotting stress and strain or angular deformation values of the three testing methods. The findings validate the vane technique as an alternative to torsion and compression for rapid textural characterization of viscoelastic foods.