Post Harvesting Technology
Mozhgan Azhdar; Narges Shahgholian; Hassan Zaki Dizaji; mansour amin
Abstract
Introduction: These days, most of the disinfectants used in the food industry such as chlorinated compounds are dangerous and harmful. Common methods of removing all types of pollution have many disadvantages for human health and the environment. It is possible to help preserve the environment and human ...
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Introduction: These days, most of the disinfectants used in the food industry such as chlorinated compounds are dangerous and harmful. Common methods of removing all types of pollution have many disadvantages for human health and the environment. It is possible to help preserve the environment and human health by replacing these methods with new ones such as ultrasound technology. Ultrasonic waves are non-thermal technology that helps increase microbial safety and prolong the shelf life of heat-sensitive foods with nutritional value and functional characteristics. Ultrasonic waves are known as one of the most effective disinfection methods for all forms of microbial and fungal contamination. These waves reduce the resistance of microorganisms by physically damaging them. Therefore, this study deals with the effect of high-power ultrasound waves on the population of two type of pathogenic microorganisms in the washing effluent of tomatoes. The selected bacteria included one type of gram-positive bacteria (Staphylococcus. aureus) and one type of gram-negative bacteria (Escherichia coli) to compare the effect of ultrasound waves on the two different types of bacteria with different cell walls. Materials and Methods: In this research, irradiation of high-power ultrasound waves were applied to the water after washing the tomatoes. In this washing effluent, the impacts of ultrasonic power (100, 300, 500 W), radiation time (300, 750, 1200 s), and water temperature (0, 30, 60 °C) were examined on the survival of the S. aureus and Ecoli. The data analysis was done for each experimental runs, using the response surface methodology (RSM), to find the best model for estimating the difference in bacterial population (CFU) before and after irradiation. Results and Discussion The lack of fit was not significant in the analysis of variance and also the value of the explanation coefficient in the model for S. aureus and Ecoli were 0.9721% and 0.9206% respectively. This indicated the appropriate accuracy of the quadratic model in estimating the number of S. aureus and Ecoli remaining in the water after washing tomatoes (for the mentioned independent variables). Gram-negative bacteria (E coli), are composed of an inner thin peptidoglycan cell wall, surrounded by an outer lipopolysaccharide membrane. Gram-positive bacteria (S. aureus), lack an outer membrane but are made up of a multi-layered and very complex structure layers of peptidoglycan many times thicker than is found in the Gram-negatives. In general, the application of ultrasound waves causes to destruction of the mentioned bacteria. The main disinfection effect of ultrasonic waves on the population of S. aureus was power, while for Ecoli the main variable was temperature (based on the highest coefficient of quadratic equations/ 99% confidence level). Through physical, chemical and mechanical effects caused by acoustic cavitation, ultrasound is able to affect the bacterial suspension without producing a side product. The antimicrobial effect of ultrasound is achieved by a combination of chemical effects such as the production of active free radicals and thermal effects such as the production of local hot spots. The observations showed that increasing the temperature first increased and then decreased the effectiveness of ultrasound waves in the inactivation of bactetria. The negative effect of increasing temperature can be related to the decrease in the intensity of bubble explosion. Conclusion: According to the results of the experimental tests in the average time (750 s), with the simultaneous decrease in temperature (from 60 to 0 ºC) and increase in power (from 100 to 500 W), the destruction effect of ultrasound waves on S. aureus and Ecoli was increased. In the perturbation curves, the simultaneous effect of all three parameters (temperature, time and power), were investigated at the middle points (30 ºC, 750 s and 300 W). At these points, power changes were more effective in reducing S. aureus population, while temperature changes were more effective on the reduction of E coli. The population of S. aureus and E. coli decreased by increasing power of ultrasonic waves. Temperature and power had a synergistic effect, that is, the increase of both parameters led to the decrease of bacteria population. Finally, the tested variables were optimized by desirability in the RSM to minimize the population of microorganisms (S. aureus and E coli simultaneously), and parameters (in the range) obtained for the ultrasonic power, time, and temperature were 300 W, 1200 s, and 0 °C respectively.
Post Harvesting Technology
mohammad Rasool Afifi; Yaghoob Mansoori; hassan zaki dizaji; Gholamreza Akbarizadeh
Abstract
Introduction Date fruit is a strategic horticultural product in the Middle East that plays an important role as an economic product to develop exports. Iran is the second world producer that contains 14% production of date fruit in the world and has a high potential in order to ideally exploit this valuable ...
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Introduction Date fruit is a strategic horticultural product in the Middle East that plays an important role as an economic product to develop exports. Iran is the second world producer that contains 14% production of date fruit in the world and has a high potential in order to ideally exploit this valuable product. Condidering the low price of Iran's exported dates due to poor preparation and packaging process it is necessary to use new technologies for classification and grading of them. The application of machine vision in agriculture has increased considerably in recent years.There are many fields in which computer vision is involved in order to develop precision agriculture. Machine vision systems by elimination of manual inspection in the field of postharvest technologies improve accurate and uniform quality control of agricultural products. In most of these applications, the method of image analysis for product categories, with the determination of some external features such as color, size, shape, and surface texture has been used (Blasco et al., 2012). Alohali used RGB images taken from Date fruits and defined a set of qualitative external features of dates and categorized them into three categories in terms of quality. One of the characteristics of the soft tissue was detected using color intensity distribution. The final precision of carefully designed system using a propagation neural network was 80% (Alohali, 2011). The size is a particular aspect of external appearance of fruits and vegetables; the price of agricultural products is usually related with their size; therefore, grading of fruits and vegetables into different size groups of size is always necessary in the postharvest handling and processing stages (Zhang et al., 2014). Texture is the other significant sensory quality attribute that has been frequently used in the external quality inspecting and grading systems for the agricultural product quality evaluation. Texture is closely related to some internal quality of fruits and vegetables, such as maturity and sugar content. Therefore, texture is one of the widely used indicators the consumer uses for quality assessment of fruits and vegetables. Texture analysis can also play an important role in defect recognition and segmentation in grading systems due to its powerful discriminating ability (Lee et al. 2008). Materials and Methods The current study examined image processing technology for grading Zahedi cultivar dates in Khuzestan province. Each date fruit was placed under the camera and imaged. At the same time, the samples were classified by an experienced grader. Imaging was conducted in a lighting box to avoid the effects of ambient light. Capturing images was done by a digital camera using CCD sensor. External features of dates such as color, size, shape and surface texture were extracted by image processing methods using MATLAB software (Version R2013a, The Mathworks Inc., Natick, MA, USA). Eleven size and shape features, nine color features, and six external texture features were extracted. The features which led to better separablity for classification were selected using stepwise discriminant analysis (SDA). Selecting the best features is effective to increase accuracy and speed of the algorithm. Two methods of learning machine were used for final classification: discriminant analysis that is a statistical technique and neural networks (ANN). Discriminant analysis method and Neural networks were implemented in SPSS 22.0 and neurosolution 7.0 software respectively. Results and Discussion The best channel to separate dates from background was identified by comparison of the histogram of 9 channels from RGB, HSI and Lab color spaces. The histogram graph, which has more breakdown in the range of intensities, is more suitable to apply thresholding operation because it has a good contrast with the background. Channel B from RGB color space was chosen to segment dates from background. Channel of B has a better contrast between the color channels and also its corresponding histogram intensity values led to the best separability. Five features of size and shape, three features of color and three features of external texture were selected by SDA method to reduce dimension of features space. Degrees marked from 1 to 3 for qualitative grading and sorting by size define levels of quality and determine size from big to small dates respectively. According to table 4, accuracy of classifications for grading, sorting by size and inspection of wrinkled date fruits from healthy ones were 93.6%, 94.4% and 90% respectively. Classifications by MLP neural networks were done. The most important factor for evaluation of neural networks is Correct classification rate (CCR%). The results based on CCR from Confusion matrix is reported in table 5. Accuracy of classifications for grading, sorting by size and inspection of wrinkled date fruits from healthy ones using ANN were 95.7%, 92.3% and 93.8% respectively. Conclusion Final accuracy of classification using discriminant analysis and neural network was achieved 92.7% and 93.9% respectively. Results show relative superiority of neural networks over statistical methods due to its accuracy. According to high accuracy of classification using learning machine methods, it can be concluded that using image processing algorithm was successful in extracting external features for sorting and grading of dates.
H. Nematpour Malikabad; M. j. Sheikhdavoodi; I. Khorasani Frdvany; H. Zaki Dizaji
H Zaki Dizaji; S Minaei; T Tavakoli Hashtjin; M Mokhtari Dizaji
Abstract
Introduction: It is known for a long time that ultrasound offers unique features in food industry and also agricultural industry for characterizing products in their intact state, with no sample preparation and no sample destruction. However, it is used still mostly in research environment and there ...
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Introduction: It is known for a long time that ultrasound offers unique features in food industry and also agricultural industry for characterizing products in their intact state, with no sample preparation and no sample destruction. However, it is used still mostly in research environment and there is little available research about fruit quality assessment by ultrasonic technique in IRAN. Knowing the quality of agricultural products not only from the perspective of export and domestic consumers is important interests, but it also helps to control and reduce its postharvest losses. Determination of the quality of agricultural products such as fruits and vegetables is important in commercially competitive modern agriculture. Physiological degradation of pomegranate results in reduced quality exhibited as peel softening and loss of freshness. Native land of the pomegranate (Punica granantum L) is IRAN and it is an important tree of the tropical and subtropical regions of the world which is valued for its delicious edible fruit. Among the native fruits grown for export, pomegranate has a special significance. According to the FAO statistical report, Iran is the first producer and exporter of pomegranate in the world. Despite its importance, its basic tissue attributes and whole fruit maturity has not been studied. On the other hand, pomegranate fruits are not maturity indicators obviously such as tomato. For this reason pomegranate was selected for the current research. In this study, ultrasonic technique is utilized as a suitable method for quality determination of pomegranate fruit. Materials and Methods: Ultrasonic technique is one of the earliest nondestructive testing (NDT) methods, which is still under development for quality determination of agricultural products. In this research, pomegranate quality was evaluated using Ultrasonic technique and punch test (Magness-Taylor). In line with previous research work, a novel ultrasonic system dubbed “Ultrasonic Qualimeter System” (UQS) and its control programs, “Ultrasonic Qualimeter System software“(UQSS) with central frequency 40 kHz were utilized to evaluate ultrasonic indices of pomegranate fruit in four quality classes of unripe(hard), ripe(medium), overripe(soft) and decayed(so soft). This ultrasonic system works based on processing the signal passing through the materials. The ordinary indices of the through-transmission ultrasonic test are wave velocity and attenuation coefficient. The other ultrasonic index is root mean square that is calculated in time zone of the digital signals. Firmness as a mechanical property, and ultrasonic wave velocity as an ultrasonic parameter, was selected to assess pomegranate quality. Evaluation of pomegranate quality was carried out through testing of its tissue and peel. The firmness index of pomegranate peels was metered by the punch test using universal material test machine (Hounsfield, H50 K-S, England). Results and Discussion: UQS were successful in transmitting ultrasound wave through pomegranate tissue (1-2 cm thickness) and peel, but results of excited and received signal processing showed that due to its non-homogenous tissue pomegranate vigorously diminished the intensity of transmitted waves. By comparison, the attenuation coefficient of pomegranate peel and its tissue is higher than that of the other agricultural products such as potato and avocado. Statistical analysis demonstrated that the quality of pomegranate fruit can be assessed using ultrasonic technique, so that decreasing freshness of pomegranate peel samples leads to decrease of wave velocity from 290 (unripe fruit) to 63 m/s (decayed fruit). In other words, depending on samples quality levels, transmitted wave velocity is varied about 230 m/s for pomegranate peel samples. One of the mechanical properties that are most useful to demonstrate fruit quality conditions is stiffness. Initially, analyses showed that Chart trend of stiffness in four quality levels is similar to wave velocity. So non-linear regression models were developed with good correlation (R2=0.83) between the firmness and ultrasonic velocity. Results of regression analysis demonstrated that ultrasonic indices of pomegranate peels can be used for inspection of pomegranate quality conditions. Conclusion: The first step in nondestructive assessment of any medium is introducing fitness index or indexes in which it can show the medium conditions. In this research, statistical analysis demonstrated that the quality of pomegranate fruit can be assessed by ultrasonic technique. However, it is necessary to carry out more research to improve this technique for widespread applications. To use this method, the ultrasonic system should be modified so that the transmitted and received transducers test the whole pomegranate by its peels.
