Prediction Of Quality Changes Research Articles

Quality Grading and Prediction of Frozen Zhoushan Hairtails in China Based on ETSFormer

With the increasing demand for high-quality, healthy, and nutritious food, hairtails have good potential for development in both domestic and international markets. In particular, Zhoushan hairtail is known as one of the best-tasting hairtail in the world for its unique composition and flavor. However, as a perishable food, the quality and safety of hairtails are susceptible to temperature and storage time. Therefore, the management of storage conditions and the prediction of quality changes in hairtails have become particularly important. In this study, Zhoushan hairtail is selected as an experimental subject, and its quality is assessed by collecting the physicochemical characteristics of hairtail at four different temperatures (−7 °C, −13 °C, −18 °C, and −23 °C) over time. Combined with the K-Means++ algorithm, we have constructed a hierarchy of hairtail quality and predicted its quality using the ETSFormer model. Through the validation of the self-constructed data set, our model has achieved good results in predicting the low, medium, and high quality of hairtails, with F1 values of 92.44%, 95.10%, and 98.01%, respectively. The model provides a theoretical basis for the scientific storage and quality regulation of Zhoushan hairtail.

Impact of thermal and thermosonication treatments of amora (Spondius pinnata) juice and prediction of quality changes using artificial neural networks

The impact of thermal and non-thermal treatments on the quality of amora ( Spondius pinnata ) juice during refrigerated storage (4 ± 1 °C) for 30 days was investigated. Freshly prepared juices from amora fruits were thermosonicated at the frequency of 44 kHz for 30, 45 and 60 min at 40 °C and also pasteurised at 90 °C for 1 min. Changes in the quality parameters, such as, pH, total soluble solids, titratable acidity, total phenolic contents, total flavonoid contents. Antioxidant activity, ascorbic acid content, browning index, cloud values and microbial populations were checked periodically. The experimental results indicated a significant increase in total phenolic contents, total flavonoid contents, antioxidant activity and the sensorial properties of thermosonicated juices during storage their period when compared to fresh and thermally treated amora juices. Maximum reduction in the microbial populations was accomplished after thermal and thermosonication for 60 min treatments. The physicochemical properties of thermosonicated juices exhibited minimal changes in contrast to other samples. The prediction of the quality changes in thermosonicated juices during storage was carried out using an artificial neural network model. From this study thermosonication at 40 °C can be recommended as a substitute to thermal processing and it may be employed to amora juice production to decrease the microbial population and improve functional and sensorial properties. • Thermosonication significantly improved the functional properties of Amora juices. • Physicochemical properties of the juices were unaffected by thermosonication. • Thermosonication extended the shelf-life of Amora juice stored at 4 °C. • Modeling of quality changes in amora juices during storage using ANN approach. • Developed ANN-PNN model was effective to predict quality changes in amora juices.

성과지향적 콘텐츠에 기반한 태권도장의 품질변화 예측에 따른 경영전략

성과지향적 콘텐츠에 기반한 태권도장의 품질변화 예측에 따른 경영전략

Assessment of groundwater and soil quality degradation using multivariate and geostatistical analyses, Dakhla Oasis, Egypt

Salinization of groundwater and soil resources has long been a serious environmental hazard in arid regions. This study was conducted to investigate and document the factors controlling such salinization and their inter-relationships in the Dakhla Oasis (Egypt). To accomplish this, 60 groundwater samples and 31 soil samples were collected in February 2014. Factor analysis (FA) and hierarchical cluster analysis (HCA) were integrated with geostatistical analyses to characterize the chemical properties of groundwater and soil and their spatial patterns, identify the factors controlling the pattern variability, and clarify the salinization mechanism. Groundwater quality standards revealed emergence of salinization (av. 885.8 mg/L) and extreme occurrences of Fe2+ (av. 17.22 mg/L) and Mn2+ (av. 2.38 mg/L). Soils were highly salt-affected (av. 15.2 dS m−1) and slightly alkaline (av. pH = 7.7). Evaporation and ion-exchange processes governed the evolution of two main water types: Na–Cl (52%) and Ca–Mg–Cl (47%), respectively. Salinization leads the chemical variability of both resources. Distinctive patterns of slight salinization marked the northern part and intense salinization marked the middle and southern parts. Congruence in the resources clusters confirmed common geology, soil types, and urban and agricultural practices. Minimizing the environmental and socioeconomic impacts of the resources salinization urges the need for better understanding of the hydrochemical characteristics and prediction of quality changes.

数値計算による凍結マグロ解凍中の品質変化の予測 －第2 報：解凍法がメト化進行度に及ぼす影響－

数値計算による凍結マグロ解凍中の品質変化の予測 －第2 報：解凍法がメト化進行度に及ぼす影響－

Prediction of Quality Change During Thawing of Frozen Tuna Meat by Numerical Calculation I

Prediction of Quality Change During Thawing of Frozen Tuna Meat by Numerical Calculation I

Moisture Diffusivity in Food and Biological Materials

The spatial distributions of water content and temperature inside moist food or biological materials (native or manufactured) during drying are important in interpretation and prediction of quality changes. The dynamics of drying in modern devices is not simple—for instance, the process of intermittent drying—thus, a liquid diffusion model is expected to be the simplest and hopefully the very effective. In this article, some controversial aspects of the concept of the effective Fickian liquid moisture diffusivity are described and discussed. These discussions are intended to stimulate more interest in working toward a better rationalization of the liquid diffusion concept. It is suggested that such a parameter may even be called a “liquid depletion coefficient” instead to avoid confusion at the fundamental level. An improved alternative model from the effective liquid diffusion model is possible and some new ideas have been explored.

Study and prediction of quality changes in garlic cv. Perla ( Allium sativum L.) stored at different temperatures

White and purple garlic is harvested in the Bajio region of Mexico from February to August and then stored at room temperature. A complete study of quality changes under different conditions and how these conditions interact to determine the shelf life of the product has been lacking, nor have objective parameters to predict shelf life been determined. Six batches of 360 bulbs of garlic ( Allium sativum L.) cv. Perla were stored for 190 days at 0 °C, 0 °C and 70% relative humidity (RH), 5, 20, 30 °C, and at room temperature (RT) (17.7 ± 7 °C). The weight loss, subjective firmness of the bulbs, clove penetration resistance, hue value, internal sprouting index, soluble solids and dry matter content of the cloves were recorded periodically. The weight loss and internal sprouting index had a negative correlation on the subjective firmness, penetration resistance, and hue of the cloves. Storage at 5 °C, 20 °C, and RT induced sprouting, and subsequent growth had an effect on a loss of firmness and color. Complete sprouting (>100%) induced a weight loss of 9–11% at these temperatures. In order to maintain an adequate safety margin for marketing, we propose an internal sprouting index of 50% to determining the effective shelf life of garlic cv. ‘Perla’. In accordance with this criterion and in conditions studying, shelf life at 0 °C was 155 days; at 5 °C and RT it was 80 days; and at 20 °C it was 60 days. These results lead us to conclude that it is possible to estimate the shelf life of garlic using the internal sprouting index.

ANALYSIS OF KINETICS OF QUALITY CHANGE IN FROZEN FOODS1

ABSTRACTTemperature fluctuations of frozen foods are of influence on frozen food quality. Prediction of quality changes under temperature fluctuations is therefore important in assuring high product quality and, by optimizing storage temperature, in conserving energy. This study is focused on applying kinetic models in analyzing Time‐Temperature‐Tolerance (TTT) data for frozen food storage and investigating the potential for use of kinetic parameters to describe quality degradation in frozen foods.Based on theoretical considerations, quality life and activation energy are related by the equation:ln tQ= ln B+Ea/R· 1/Twhere B is a function of the pre‐exponential of Arrhenius equation, initial and end point quality magnitude.Reasons for some TTT data to deviate from this relationship are: Different standards for measuring quality lives of different storage temperatures or experiments. Negative effect of temperature. Variations in initial or final quality magnitudes for a given experiment. Variations in packaging material and other factors influencing the quality magnitude or mode. ITT experiments are suitable approaches for obtaining activation energy constants, although they are not applicable for determination of reaction order and rate constant. When dealing with overall quality life of several contributing factors, quality life for each component is needed to get a better description. Quality changes in terms of fraction of initial quality magnitude retained can be described by quality life, activation energy, temperature history and the constant, α= CtQ/C0.