Ixiolirion tataricum anthocyanins-loaded biocellulose label: Characterization and application for food freshness monitoring

Author(s):  
Nima Ghadiri Alamdari ◽  
Samira Forghani ◽  
Sorour Salmasi ◽  
Hadi Almasi ◽  
Mehran Moradi ◽  
...  
Keyword(s):  
Author(s):  
Lisa Rita Magnaghi ◽  
Giancarla Alberti ◽  
Chiara Milanese ◽  
Paolo Quadrelli ◽  
Raffaela Biesuz

Membranes ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 242
Author(s):  
Yahui Meng ◽  
Yunfeng Cao ◽  
Kaifeng Xiong ◽  
Li Ma ◽  
Wenyuan Zhu ◽  
...  

As an important functional material in food industry, intelligent packaging films can bring great convenience for consumers in the field of food preservation and freshness detection. Herein, we fabricated pH-sensing films employing hydroxypropyl guar (HPG), 1-butyl-3-methylimidazolium chloride (BmimCl), and anthocyanin (Anth). Besides, the effects of adding cellulose nanocrystals (CNC) into the composite films upon the films’ structures and physicochemical properties are elucidated. The addition of CNC promoted more compact film structures. Moreover, CNC dramatically improved several properties of the pH-sensing films, including the distinguishability of their color changes, sensitivity to pH, permeability to oxygen and water vapor, solvent resistance, durability, and low-temperature resistance. These results expand the application range of pH-sensing films containing CNC in the fields of food freshness detection and intelligent packaging.


Talanta ◽  
2021 ◽  
pp. 122706
Author(s):  
Huan Li ◽  
Jiacheng Gan ◽  
Qing Yang ◽  
Linglin Fu ◽  
Yanbo Wang

2019 ◽  
Vol 6 (2) ◽  
pp. 161-174 ◽  
Author(s):  
Tharindu Athauda ◽  
Nemai Chandra Karmakar

AbstractThe changes in physical environmental parameters have severe impacts on food safety and security. Therefore, it is important to understand micro-level physical parameter changes occurring inside food packages to ensure food safety and security. The emergence of smart packaging has helped to track and inform the specific changes such as a change in humidity, temperature, and pH taken place in the microenvironment in the food package. Moreover, these key physical parameters help determine the freshness of the food as well. Radio-frequency identification (RFID)-based sensors are an emerging technology that has been used in smart packaging to detect changes in the physical stimuli in order to determine food freshness. This review looks at the key environmental factors that are responsible for food safety and food freshness, the role of smart packaging with sensors that can measure changes in physical stimuli in the microclimate and the detailed review of RFID-based sensors used in smart packaging for food-freshness applications and their existing limitations.


2020 ◽  
Vol 990 ◽  
pp. 318-324
Author(s):  
Arie Listyarini ◽  
Windri Handayani ◽  
Vivi Fauzia ◽  
Cuk Imawan

Ammonia is one of the compounds released during the food spoilage process, so a device that can detect ammonia can be used as an indicator of food spoilage. This article reports on the preparation and characteristics of Starch/PVA composite films with Syzygium oleana as indicator films to detect ammonia vapor. The indicator was made by first preparing the starch / PVA composite films by casting method and then the films were dipped in Syzygium oleana extract. These films were characterized by using a UV-Vis spectrophotometer, Fourier Transformed Infra-Red Spectrophotometer and tested for mechanical properties such as tensile strength and elongation, and the water vapor transmission rate (WVT). The results showed that the addition of PVA reduced the absorbance value in the UV and visible area, the value of the water vapor transmission rate and the tensile strength but the elongation value of the film on the other hand rose. The indicator films can detect ammonia which was marked by its color change from red to blue. For further application, it can be used as a smart packaging label that can detect food freshness.


Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4299 ◽  
Author(s):  
Eui Jung Moon ◽  
Youngsik Kim ◽  
Yu Xu ◽  
Yeul Na ◽  
Amato J. Giaccia ◽  
...  

There has been strong demand for the development of an accurate but simple method to assess the freshness of food. In this study, we demonstrated a system to determine food freshness by analyzing the spectral response from a portable visible/near-infrared (VIS/NIR) spectrometer using the Convolutional Neural Network (CNN)-based machine learning algorithm. Spectral response data from salmon, tuna, and beef incubated at 25 °C were obtained every minute for 30 h and then categorized into three states of “fresh”, “likely spoiled”, and “spoiled” based on time and pH. Using the obtained spectral data, a CNN-based machine learning algorithm was built to evaluate the freshness of experimental objects. In addition, a CNN-based machine learning algorithm with a shift-invariant feature can minimize the effect of the variation caused using multiple devices in a real environment. The accuracy of the obtained machine learning model based on the spectral data in predicting the freshness was approximately 85% for salmon, 88% for tuna, and 92% for beef. Therefore, our study demonstrates the practicality of a portable spectrometer in food freshness assessment.


Author(s):  
Rajina R. Mohamed ◽  
Razali Yaacob ◽  
Mohamad A. Mohamed ◽  
Arniyati Ahmad ◽  
Munir Tajuddin

<p>For the past few years, food safety incidents often occur as a result of food poisoning from various food sources such as in schools, hospitals, night markets, street stalls and the like. When the quality of food is reduced due to the low level of freshness, cleanliness factor, safety and nutrition, it can contribute to health risks. According to World Health Organization, food poisoning ailment is a global problem and almost 1 in 10 people fall ill every year from eating degraded food and 420 000 die as a result. Factors such as cost savings, low awareness on food freshness and busy routine lifestyle aggravate the food poisoning problem. Hence it is important to at least maintain the freshness of the food mainly at the prominent area such as school and hospital. There are many methods used to test the freshness food, such as visual appearance, and also classical olfaction including normal olfactory and Scentometer, which requires trained panels to taste or smell the food samples to ensure the quality or strength of the odor. However, this method is rather subjective, because the human sense of smell and taste is different and may be influenced by the weather and experience. Conventional pH and litmus paper also are the alternatives, however the material itself is easily damaged and not suitable for the color blind person. In this paper, we presented raw meat examination using pH sensor based on food acidity. Examination of food freshness level is much easier using pH sensor since it is more practical to be used by consumers at home since it can be mobile, long lived, and accurate embedded-based application. Some testing has been conducted on sensor capability reacting with several buffer solutions on meat samples left at room temperature at various periods of time. Generally, the embedded pH sensor developed has successfully tested raw meat freshness level based on acidity level of meat.</p>


2021 ◽  
Vol 9 ◽  
Author(s):  
Xiaojun Lyu ◽  
Wei Tang ◽  
Yui Sasaki ◽  
Jie Zhao ◽  
Tingting Zheng ◽  
...  

Herein, a self-assembled colorimetric chemosensor array composed of off-the-shelf catechol dyes and a metal ion (i.e., Zn2+) has been used for the sulfur-containing amino acids (SCAAs; i.e., glutathione, glutathione disulfide, L–cysteine, DL–homocysteine, and L–cystine). The coordination binding–based chemosensor array (CBSA) fabricated by a competitive assay among SCAAs, Zn2+ ions, and catechol dyes [i.e., pyrocatechol violet (PV), bromopyrogallol red (BPR), pyrogallol red (PR), and alizarin red S (ARS)] yielded fingerprint-like colorimetric changes. We succeeded in the qualification of SCAAs based on pattern recognition [i.e., a linear discrimination analysis (LDA)] with 100% correct classification accuracy. The semiquantification of reduced/oxidized forms of SCAAs was also performed based on LDA. Furthermore, we carried out a spike test of glutathione in food samples using the proposed chemosensor array with regression analysis. It is worth mentioning that we achieved a 91–110% recovery rate in real sample tests, which confirmed the accuracy of the constructed model. Thus, this study represents a step forward in assessing food freshness based on supramolecular analytical methods.


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