An application of image analysis and colorimetry methods to colour change on dried asparagus (Asparagus maritimus L.) (original) (raw)
Related papers
Shape and color are key factors in quality evaluation of fresh asparagus (Asparagus maritimus L.). Typical green color of asparagus comes from the chlorophyll, pigment which has been degradated during drying process. The aim of this paper was to compare color changes of asparagus dried in laboratory tray drier equipment at different temperatures (40 °C, 50 °C, 60 °C and 70 °C) at airflow velocity of 2.75 ms-1. Color changes were obtained by digital image analysis in RGB color model and by chromameter in L*a*b* color model. Basic elements of image analysis system were low voltage halogen lamps with reflector, digital camera and programs for image pre-processing and analysis. Mean values of color parameters, color changes and correlation coefficients for asparagus were calculated for both color models. An analysis showed statistically significant influence of drying temperature on hue angle and total color change for both chosen color models of dehydrated asparagus. Represented result...
Color Analysis of Carrots and Lemons by Using Spectrophotometer
This research was carried out to assess the distribution of color in carrots, green lemons and yellow lemons for quality estimation. The color measurements of these fruits and vegetable were taken from a coordinate system of points on the surface. A Minolta Spectrophotometer (CM-508i) was used to measure a* and b* in the CIE L *a*b* color model with the standard illuminant (D 65 ) and spectral wave of reflectance in visible range (400-700) nm. For color analysis using the Coefficient of Variation (CV) as an indicator of color homogeneity, carrots and yellow lemons were found to have lower CV values of a* and b* than the green lemons. From the result of CV analysis of the spectral wave of reflectance in visible range, the carrots and yellow lemons only had primary color that a single measurement point of color may be possible. On the other hand, green lemons having a secondary color required more measurement points to accurately describe the color of the fruits.
Authentication of Green Asparagus Varieties by Near‐Infrared Reflectance Spectroscopy
Journal of Food Science, 2001
ABSTRACT: Near‐infrared reflectance spectroscopy (NIRS) was used for the authentication of 2 green asparagus varieties (Taxara and UC‐157), grown in Huetor‐Tajar (Granada, Spain) protected by the Quality Specific Appellation “Espárragos de Huétor‐Tájar”. To develop the prediction model, the method chosen was modified partial least square (MPLS) regression. Two sample sets (N = 219 and N2 = 145 samples, respectively) were used to obtain the calibration equations. The standard error of cross‐validation (SECV) and the r2 value were 0.082 and 0.97, respectively, for the 1st calibration set and 0.077 and 0.97 for the 2nd calibration set. The 2nd chemometric model obtained was tested with independent validation sample set (N3 = 74 samples), and the resulting values for standard error of prediction (SEP) and for r2 were 0.07 and 0.96, respectively. These results prove that NIRS is an accurate technology for identification and authentication of asparagus varieties and easily implemented in ...
Quantitative assessment of intact green asparagus quality by near infrared spectroscopy
Postharvest Biology and Technology, 2009
NIR spectroscopy was used to assess textural parameters (maximum shear force and cutting energy) in intact green asparagus. At the same time, two commercially available spectrophotometers, which differ primarily in terms of measurement principles, were evaluated: a scanning monochromator (SM) of 400-2500 nm and a combination of diode array and scanning monochromator (DASM) of 350-2500 nm. A total of 468 green asparagus spears cv. 'UC-157' were used to obtain calibration models based on reference data and NIR spectral data. Both instruments provided good precision for maximum shear force, with r 2 values between 0.55 and 0.67 and standard error of cross-validation (SECV) ranging from 7.81 to 8.43 N, and also for cutting energy (r 2 = 0.60-0.74; SECV = 0.06-0.07 J). The results obtained suggest that NIR spectroscopy is a promising technology for predicting intact green asparagus quality in terms of texture. They also show that the two spectrophotometers tested provided a similar degree of accuracy for texture measurements in intact green asparagus.
Colour Measurement and Analysis in Fresh and Processed Foods: A Review
Colour is an important quality attribute in the food and bioprocess industries, and it influences consumer’s choice and preferences. Food colour is governed by the chemical, biochemical, microbial and physical changes which occur during growth, maturation, postharvest handling and processing. Colour measurement of food products has been used as an indirect measure of other quality attributes such as flavour and contents of pigments because it is simpler, faster and correlates well with other physicochemical properties. This review discusses the techniques and procedures for the measurement and analysis of colour in food and other biomaterial materials. It focuses on the instrumental (objective) and visual (subjective) measurements for quantifying colour attributes and highlights the range of primary and derived objective colour indices used to characterise the maturity and quality of a wide range of food products and beverages. Different approaches applied to model food colour are described, including reaction mechanisms, response surface methodology and others based on probabilistic and non-isothermal kinetics. Colour is one of the most widely measured product quality attributes in postharvest handling and in the food processing research and industry. Apart from differences in instrumentation, colour measurements are often reported based on different colour indices even for the same product, making it difficult to compare results in the literature. There is a need for standardisation to improve the traceability and transferability of measurements. The correlation between colour and other sensory quality attributes is well established, but future prospects exist in the application of objective non-destructive colour measurement in predictive modelling of the nutritional quality of fresh and processed food products.
Journal of Food Science, 2009
The effect of different types of lighting (white, green, red, and blue light) on minimally processed asparagus during storage at 4 • C was studied. The gas concentrations in the packages, pH, mesophilic counts, and weight loss were also determined. Lighting caused an increase in physiological activity. Asparagus stored under lighting achieved atmospheres with higher CO 2 and lower O 2 content than samples kept in the dark. This activity increase explains the greater deterioration experienced by samples stored under lighting, which clearly affected texture and especially color, accelerating the appearance of greenish hues in the tips and reddish-brown hues in the spears. Exposure to light had a negative effect on the quality parameters of the asparagus and it caused a significant reduction in shelf life. Hence, the 11 d shelf life of samples kept in the dark was reduced to only 3 d in samples kept under red and green light, and to 7 d in those kept under white and blue light. However, quality indicators such as the color of the tips and texture showed significantly better behavior under blue light than with white light, which allows us to state that it is better to use this type of light or blue-tinted packaging film for the display of minimally processed asparagus to consumers.
2020
The first thing the consumer uses without tasting the fruit is the sense of sight. Human vision can be replaced by a digital camera and under specific conditions we can measure the color parameters of fruits. The color determination of Tommy Atkins mango, papaya, star fruit and golden berry were performed using the standardized computer vision system. High coefficients of determination (R 2) were obtained, explained by the linear regression model, for parameter L* (0.9986), for parameter a* (0.9992) and for parameter b* (0.9991). The CIE L*a*b* parameters for Tommy Atkins mango (L* = 74%, a* = 78.3% red, b* = 55% yellow), papaya (L* = 74%, a* = 15% of green, b* = 43.3% of yellow), star fruit (L* = 59%, a* = 18.3% of red, b* = 61.7% of yellow) and golden berry (L* = 67%, a* = 16.7% of red, b* = 85% of yellow).
2013
Colour is an important sensory attribute for acceptance of food products. For maintaining uniform colour and appearance of products, proper methods of colour measurement are essential. Some of the instruments commonly being used are colorimeters, spectrophotometers, comparator charts or colour discs which proved to be useful tools for colour measurement. However, objective colour measurement methods have undergone significant changes in recent years with advancements in computer hardware and software and digitization technology. Flatbed scanners, cameras, various software like Adobe Photoshop are finding increased applications for colour measurement and monitoring. Fundamentals of computer vision and applications in various food products are reviewed here.
Calibrated color measurements of agricultural foods using image analysis
Postharvest Biology and Technology, 2006
A computer vision system (CVS) was implemented to quantify standard color of fruit and vegetables in sRGB, HSV and L * a * b * color spaces, and image capture conditions affecting the results were evaluated. These three color spaces are compared in terms of their suitability for color quantification in curved surfaces. The results show that sRGB standard (linear signals) was efficient to define the mapping between R G B (no-linear signals) from the CCD camera and a device-independent system such as CIE XYZ. The CVS showed to be robust to changes in sample orientation, resolution, and zoom. However, the measured average color was shown to be significantly affected by the properties of the background and by the surface curvature and gloss. Thus all average color results should be interpreted with caution. L * a * b * system is suggested as the best color space for quantification in foods with curved surfaces.
Experimental RGB and CIE L*a*b* colour space analysis and comparison for fruits and vegetables
Journal of emerging technologies and innovative research, 2017
Colour indicates the freshness and dryness of fruits and vegetables. Many colour space are available to measure the approximate colour value of natural food items. This experiment deals with comparison of colour reproduce by RGB colour space value and CIE L*a*b* colour space value. Fruits and vegetables sample of different colour shades where selected and their high definition photos were taken and converted into RGB colour space and CIE L*a*b* colour space using MATLAB 2015a V2.1 and reproducing the colour in Adobe Photoshop Creative Studio 6 V13.0.1. The colour reproduced shows that colour obtain by RGB colour value appears more balanced in hue and saturation as compare to those colour obtain by CIE L*a*b* colour space value. But it is more convenient to use CIE L*a*b* colour space because its colour coordinates can explain the level of saturation and hue in numerical way.