VISUAL CHARACTERIZATION OF THE ESTHETIC QUALITY OF THE ROSEBUSH

Since its introduction into the analysis of foodstuffs, sensory analysis has been applied in several contexts. This work seeks to widen the field of sensory analysis to include ornamental plants and to characterize their esthetic quality. Using the rosebush as a plant model, an attribute generation protocol is proposed in order to develop a conventional profile of such products. Further to statistical treatments aiming to verify the unambiguity, discrimination and independence of these attributes, a reduced list of 18 attributes has been set up. These attributes make up the very core of the conventional profiling studies currently undertaken .

PRACTICAL APPLICATIONS

The generation of a list of attributes that is not too long, in order to describe plants as exhaustively as possible, is one of the first steps of extending sensory analysis methods to ornamental horticulture. This list will be used to train a panel of assessors to characterize the rosebush.
Two applications are in progress. The first application consists of evaluating the impact of nitrogen nutrition on the visual quality of the rosebush. The second has the objective of determining which characteristics influence consumer preferences.     

USE OF TACTILE AND VISUAL CUES IN CONSUMER JUDGMENTS OF APPLE RIPENESS

The relative importance of visual and tactile cues in consumer assessments of'Royal Gala'apple ripeness were studied in relation to commercial maturity indices which included background color, blush, weight and skin greasiness. Apples were evaluated by consumers under 3 sensory conditions to isolate their use of visual and tactile cues. Individual fruit were harvested to provide apples which independently varied in background color, blush and weight. Visual cues of skin color were found to be greater drivers of perceived apple ripeness than tactile cues of skin greasiness and apple firmness. Amongst the visual cues tested, the hue of the background color had the greatest impact on consumer judgments of'Royal Gala'apple ripeness. Consumer's ideal'Royal Gala'apple ripeness was achieved with a background color between chip levels 5 and 8, blush coverage between 33-66% and weighing between 130-142 g.     

SENSORY EVALUATION OF VANILLA-DAIRY DESSERTS BY REPERTORY GRID METHOD AND FREE CHOICE PROFILE

“Natillas” are semisolid dairy desserts widely consumed in Spain, with notable differences existing between commercial brands in their composition and sensory and physical properties. The repertory grid method, in conjunction with the free choice profile (FCP), was used to provide data on how consumers perceived eight commercial “natillas” samples. The most frequent terms used were: vanilla flavor, sweetness, consistency and liquid texture as described by 77, 67, 57 and 53% of the consumers, respectively. A three‐dimensional solution was chosen. Dimension 1 accounted for 27.23% of variance and separated the samples largely by yellow‐color intensity and consistency. Dimension 2 (15.88%) was mainly related to the visual attributes of texture, creaminess and different notes of flavor. The third dimension (11.34%) was related to structural‐texture attributes, orange‐yellow color and acid and artificial flavors. The assessors plot showed two clusters. Analysis of each group data revealed differences in their perception of sample variation, mainly regarding texture and color.     

Assessing the assessors: Quantifying observer variation in vegetation and habitat assessment

Vegetation assessment protocols used in research, monitoring and statutory planning often rely on the consistent application of methods by multiple assessors. Consequently, a study was undertaken to evaluate the application of a vegetation condition assessment protocol by a range of assessors. The aim of the study was to quantify variation among assessors in their measurement of field‐based vegetation attributes using Queensland’s BioCondition protocol, and to determine the effect of variability on the final condition score. The study consisted of 77 assessors, ranging from nil to 25 years experience in vegetation assessment, who each undertook an assessment at one site following training. Six of the 20 attributes used to derive the final condition score were not assessed consistently, this being because of a small number of assessors who had misinterpreted the protocol and had inappropriately assessed some attributes. Despite inclusion of outliers, 82% of assessors were within 10 points of the median condition score for the site. Based on the results, the definition and measurement of problematic attributes have been either clarified or removed from the revised assessment procedure. The study demonstrated that with training prior to use, assessors were able to consistently assess condition at the study site.     

SENSORY AND INSTRUMENTAL EVALUATION OF STRAWBERRY YOGURT COLOR

Eleven samples of strawberry yogurt prepared with different red color concentrations using Ponceau 4R (E-124) were evaluated by instrumental and sensory methods. Color intensity evaluation was carried out by a panel of eight assessors specifically trained to measure strawberry color in yogurt. Color acceptability was measured with 120 regular and frequent consumers of yogurt. Color was measured with a Minolta Chroma Meter CR-200b, obtaining parameters L*, a* and b*. Principal component analysis was performed on the instrumental variables. Regression models between the instrumental first principal component, red color concentration, sensory intensity, and acceptability allowed determining quality control limits for red color attribute. These limits may be controlled by selecting either instrumental or sensory methods, being the latter easy to implement and providing dependable results.     

SENSORY PROPERTIES AND CONSUMER PERCEPTION OF 'HOME-MADE'AND COMMERCIAL DAIRY ICE CREAM

Sensory properties and consumer perception of 2 'home-made'and 4 commercial dairy ice creams were examined. Conventional profiling by a trained panel found that most samples differed significantly in all attributes, but distinction of 'home-made'from commercial products was limited to few attributes. Principal component analysis separated the 'home-made'products from the commercial ones mainly on the basis of differences in appearance, aroma, creamy flavors and textural attributes. A consumer group (n=105) recorded preconception of 'home-made'ice cream acceptance, then received the product samples, in unlabeled condition, for assessment of degree of liking (DOL) and for identification as 'home-made'or commercial. Internal preference mapping of the DOL ratings showed that consumers were more closely grouped around samples which had higher intensities of certain attributes. Higher 'denseness', 'vanilla'aroma and 'buttery'flavor, were associated with more liking for commercial products. The 'home-made'high fat sample, although liked, tended to be grouped with commercial products. More marked textural attributes of 'ice crystals'and 'breakage'aided identification of the low-fat 'home-made'formulation, which was less liked overall. Overall, differences between the 'home-made'and commercial samples were small but consumer perception of the term 'home-made'was viewed favorably for dairy ice cream.     

The critical cue in pattern discrimination for the honey bee: Color or form?

When honey bees approach blossoms, they are attracted by the color and form of the goal in their visual field, and they use these cues for a successful revisit. Their visual system receives cues by two main types of parallel channels behind the retina; one channel for colors, and a monochrome channel for the orientation and edge of the item in their visual field. In the integration process of these 2 channels, the priority and interaction between them are significant due to the fact that these chromatic and achromatic signals coexist naturally. To investigate this issue, we trained bees to detect form and color and then tested them with combinations of opposite patterns. We observed that the bees chose the correct color but the wrong form pattern in the above experiment as well as for other manipulations as follows. The effect of the color training for the blue reward pattern differed from that of the green reward pattern. The color pattern choices tended to be more correct if blue was the target during the training process, indicating that the chromatic signal was the main cue in pattern discrimination. In other words, color tended to be the decisive factor in a conflicting situation. In addition, the color blue was preferred over the color green, indicating that color preference was involved in visual recognition.     

Evaluation of hawthorns maturity level by developing an automated machine learning-based algorithm

Marketability of agricultural products depends heavily on appearance attributes such as color, size, and ripeness. Sorting plays an important role in increasing marketability by separating crop classes according to appearance attributes, thus reducing waste. As an expert technique, image processing and artificial intelligence (AI) techniques have been applied to classify hawthorns based on maturity levels (unripe, ripe, and overripe). A total of 600 hawthorns were categorized by an expert and the images were taken by an imaging box. The geometric properties, color and, texture features were extracted from segmented hawthorns using the Gray Level Co-occurrence Matrix (GLCM) and evaluation of various color spaces. The efficient feature vector was created by QDA feature reduction method and then classified using two classical machine learning algorithms: Artificial Neural Network (ANN) and Support Vector Machine (SVM). The obtained results indicated that the efficient feature-based ANN model with the configuration of 14–10-3 resulted in the accuracy of 99.57, 99.16, and 98.16% and the least means square error (MSE) of 1 × 10⁻³, 8 × 10⁻³, and 3 × 10⁻³ for training, validation and test phases, respectively. The machine vision system combined with the machine learning algorithms can successfully classify hawthorns according to their maturity levels.     

A COMPARISON OF METHODS FOR MONITORING INDIVIDUAL PERFORMANCES IN TASTE SELECTION TESTS

The evaluation of panel performance was made by three methods: average of correct responses (A), comparison of distances of individual standardized judgments to the average standardized responses (D) and a principal components analysis (PCA). Thirty assessors identified water and basic tastes and discriminated different sweet stimuli in neutral or acidified vehicles using R‐index rating and ranking tests. By A and D methods 22 assessors were qualified as proficient. Composition of both panels was identical except for one judge. The output from PCA provided a graphical representation of the performance of the assessors and retained different subsets of 24–26 panelists for different proposals as discrimination of sweetness in acidified beverages, recognition of bitterness, sourness and discrimination of slight sweetness or evaluation of saltiness.     

TRAINING, VALIDATION AND MAINTENANCE OF A PANEL TO EVALUATE THE TEXTURE OF DRY BEANS (PHASEOLUS VULGARIS L.)

The inclusion of dry beans in diets has clear health benefits. However, consumers in developed countries mainly choose beans for their sensory qualities, especially for their texture. This article describes the constitution, training and validation of a panel of judges to evaluate the texture of dry beans. The judges were trained in the perception of different textures, analyzed a wide range of beans and selected seed-coat roughness, seed-coat perceptibility and creaminess/mealiness of the cotyledon as the main attributes to be scored. After training, the panel was capable of discriminating between different varieties of beans and even between beans of the same variety grown at different locations. The analysis of the behavior of the panel in a standard tasting session 2 years after its formation showed that periodic inclusion of samples from the extremes of the scales for the attributes during tasting sessions was sufficient to keep the panel trained.

PRACTICAL APPLICATIONS

This article could serve as a guide for the training of sensory panels to evaluate the texture of dry beans. It describes the selection of the attributes on which the analysis is based, references for the extreme values of the attributes and how to train the panel. It also provides a practical example of the analysis of the behavior of the panel some time after training.