Research Article-en
Food Chemistry
Amir Kazemi; Asghar Mahmoudi; Seyyed Hossein Fattahi
Abstract
Different varieties of wheat as one of the strategic crops are cultivated in Iran based on the specific geographical and climatic conditions of each area. Classification of wheat varieties is important in order to guarantee the final products acquired from wheat flour. Fourier Transform-Mid Infrared ...
Read More
Different varieties of wheat as one of the strategic crops are cultivated in Iran based on the specific geographical and climatic conditions of each area. Classification of wheat varieties is important in order to guarantee the final products acquired from wheat flour. Fourier Transform-Mid Infrared (FT-MIR) spectroscopy as a nondestructive approach combined with chemometrics was employed to classify four varieties of Iranian wheat. 160 samples were analyzed and various preprocessing algorithms were used to correct unwanted information. Then, Principal Component Analysis (PCA) as unsupervised and Support Vector Machine (SVM) as supervised models with Max-Relevance Min-Redundancy (MRMR) feature selection algorithm were applied to investigate the classification of these varieties. The best result of SVM model without feature selection was with S-G+D2+MSC preprocessing with 99.4% of accuracy. The output of 100% with SVM model and MRMR feature selection algorithm confirmed the capability of FT-MIR spectroscopy method for classification of Iranian wheat flour varieties.
Research Article-en
Food Engineering
Mohammad Nasiri-Galeh; Mahdi Ghasemi-Varnamkhasti
Abstract
Electronic nose is an electronic device for smell detection. The data obtained from this device are stored in the form of numbers in different columns, which are related to the data of two types of cheese namely gluten-free cheese and cheese with gluten. It is not enough to make decisions and judge ...
Read More
Electronic nose is an electronic device for smell detection. The data obtained from this device are stored in the form of numbers in different columns, which are related to the data of two types of cheese namely gluten-free cheese and cheese with gluten. It is not enough to make decisions and judge the data unless discovering the relationships and patterns between the data obtained to determine the relation of new data recorded by the device to the type of cheese, For this purpose, data mining and machine learning methods have been used in this research. Data mining includes various algorithms such as classification, clustering, and obtaining association rules. To get a better result from the data, a data mining process was performed on 105 different permutations of the models, and 13 models with the highest accuracy in understanding the relationships between the data were chosen. In this research, with data mining methods, cheese with gluten and gluten-free cheese data were classified into separate categories, and a model was created to predict the type of new input data in terms of the nature of cheese (gluten-free and with gluten). With analyzing 105 Permutations, Finally, the best suitable model to be used for data classification using the Random Forest algorithm and MinMaxScaler for scaling was selected with a prediction accuracy of 99.8% for both test and training datasets.
Research Article-en
Food Technology
Zeinab Moslehi; Marzieh Bolandi; Seyedhamidreza Ziaolhagh; Sima Bani
Abstract
Edible coatings can be an effective and environmentally friendly method for preserving food quality during storage. This concept sets the research stage that explores how coatings made from soy protein concentrate and whey protein can enhance the chemical stability of potato slices, thus improving their ...
Read More
Edible coatings can be an effective and environmentally friendly method for preserving food quality during storage. This concept sets the research stage that explores how coatings made from soy protein concentrate and whey protein can enhance the chemical stability of potato slices, thus improving their preservation and overall quality during storage. The study lays the groundwork for investigating the effects of these coatings on various physicochemical properties of semi-dried potatoes, ultimately highlighting their potential benefits in food preservation. In this research, the impact of different concentrations (2.5, 4, and 5 w/w %) of soy protein concentrate and whey protein on some physicochemical properties of semi-dried potatoes (color, rehydration of dried slices, reducing sugars, starch, ascorbic acid, moisture, oil absorption, texture crispness, and sensory properties) during 60 days of storage were investigated. The results showed that semi-dried potatoes coated with soy protein concentrate and whey protein had the highest moisture content and the lowest oil absorption and crispiness compared to the control sample. The sensory properties of coated samples were different from those of uncoated samples. Panelists also accepted the taste of coated semi-dried potatoes. The applied edible coatings significantly affected the ascorbic acid and reducing sugar content. The lowest and highest amount of starch was observed in the control and coated samples, respectively. These characteristics show that coatings based on soy protein concentrate and whey protein considered to be an excellent choice to reduce oil absorption and increase shelf life of potato slices.
Research Article-en
Food Technology
Behdad Shokrollahi Yancheshmeh; Mehdi Varidi; Seyed Mohammad Ali Razavi; Farshad Sohbatzadeh
Abstract
Soybeans, a prominent legume, offer substantial health benefits due to their rich and beneficial nutritional profile. However, the food sector requires improved protein functions. The functional and physicochemical characteristics of isolates from four widely grown soybean cultivars in Iran, namely Katul, ...
Read More
Soybeans, a prominent legume, offer substantial health benefits due to their rich and beneficial nutritional profile. However, the food sector requires improved protein functions. The functional and physicochemical characteristics of isolates from four widely grown soybean cultivars in Iran, namely Katul, Sahar, Tellar, and Sari, were examined in this research. The proximate analysis revealed significant differences (p<0.05) among the cultivars in moisture, ash, protein, and fat contents, with Katul isolates showing the highest protein (90.75%) and lowest fat (3.67%) content. Color analysis indicated significant variations in brightness (L*), with Katul isolates being the brightest due to lower fat and ash content. Surface hydrophobicity varied significantly among cultivars, with Sahar showing the highest value (360.30 a.u.). Protein solubility was highest for Katul protein isolate (69.43%), influencing functional properties like emulsification and foaming. Cultivar-specific differences were observed in both water absorption capacity (WAC) and oil absorption capacity (OAC), with Tellar exhibiting the highest OAC (2.42 g/mL). Emulsifying properties, evaluated through emulsion stability (ES) and emulsion capacity (EC), were highest for Sari and Katul protein isolates. Foaming properties varied significantly among the samples, so that Katul protein isolate exhibiting the highest foaming capacity (180.50%) and foaming stability (66.3%), likely attributed to its high protein content. Rheological analyses revealed that Katul had the highest consistency index (K) and shear-thinning properties, while Sahar exhibited a more Newtonian-like flow behavior. Gelation studies identified Katul as the most efficient, with the lowest gelling concentration (10%), compared to Sahar’s highest value (14%). These findings demonstrate the effect of soybean cultivar on the compositional and functional characteristics of protein isolates, suggesting potential applications in various food products depending on desired functional characteristics.
Research Article-en
Food Technology
Afsaneh Ansari; Mohammad Saadatian; Ramin Haji-Taghilou; Kadhim Sedeeq; Rawen Abdulhadi; Abdulsameea Majeed
Abstract
This study investigated the impact of melatonin treatments (1 mM and 2 mM) on the post-harvest quality of orange fruit during 30 and 60 days of cold storage. Parameters such as titratable acidity (TA), total soluble solids (TSS), vitamin C, antioxidant capacity, total phenolic compounds (TPC), total ...
Read More
This study investigated the impact of melatonin treatments (1 mM and 2 mM) on the post-harvest quality of orange fruit during 30 and 60 days of cold storage. Parameters such as titratable acidity (TA), total soluble solids (TSS), vitamin C, antioxidant capacity, total phenolic compounds (TPC), total flavonoids compounds (TFC), enzymatic activities (PAL, CAT), and color were evaluated. Melatonin significantly improved fruit quality by maintaining higher levels of total soluble solids, vitamin C, and antioxidant capacity. Both treatments effectively reduced weight loss and enhanced the activity of antioxidant enzymes. While 2 mM melatonin showed greater efficacy in the initial stages of storage, 1 mM demonstrated better stability in maintaining quality over extended periods. Melatonin treatments also influenced color parameters, suggesting potential improvements in visual appeal. These findings highlight the potential of melatonin as a natural preservative for enhancing the post-harvest quality and extending the shelf life of orange fruit. Further research is needed to optimize melatonin concentrations and explore its integration with other preservation techniques for sustainable and efficient fruit management.
Review Article-en
Food Biotechnology
Hossein Mirzaei-moghaddam; Arian Nahalkar; Ahmad Rajaei
Abstract
This article reviews the antioxidant and antimicrobial properties of biodegradable edible films based on Pickering emulsions containing essential oils. Edible biodegradable films incorporating essential oil-loaded Pickering emulsions are increasingly recognized as a promising option for sustainable food ...
Read More
This article reviews the antioxidant and antimicrobial properties of biodegradable edible films based on Pickering emulsions containing essential oils. Edible biodegradable films incorporating essential oil-loaded Pickering emulsions are increasingly recognized as a promising option for sustainable food packaging. By incorporating essential oils into the emulsion matrix, the antioxidant and antimicrobial properties of these films significantly improved. Therefore, the key properties discussed in this review include antioxidant activity, antimicrobial effectiveness, and the role of these films in extending the shelf life of food products. The results showed that the incorporation of Pickering emulsions containing essential oils significantly increased the antioxidant capacity of the films, leading to a notable reduction in oxidative degradation of food. Additionally, these films exhibited effective antimicrobial activity against various foodborne pathogens such as Escherichia coli and Staphylococcus aureus, which is attributed to the bioactive properties of the incorporated essential oils. The films effectively inhibited microbial growth, directly contributing to enhanced food safety. The findings highlight the great potential of Pickering emulsion-based biodegradable films as a sustainable solution for food packaging with antioxidant and antimicrobial properties, ensuring longer shelf life and higher safety of packaged food products.