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Inventory issues involving quality degradation are complex to resolve and harm company performance. This study proposes an integrated production-inventory model for multi-item raw materials with exponential quality degradation. The proposed model is based on a finished product that requires several materials that degrade quality in the food industry. The proposed model's objective function is to maximize profits using the decision variables and an optimal number of raw material shipments ( m j ), production time cycle (T ), and the number of finished product shipments (n ). The grey wolf optimizer (GWO) algorithm is proposed in this study to solve this problem. A case study was conducted on the Indonesian food industry, which produces a finished product from five raw materials. The results demonstrated that the proposed GWO algorithm could solve the production-inventory model problem. A sensitivity analysis of the research is also presented to investigate the impact of changes in the variable rate of quality degradation (k ), rate of production (P ), and demand (D ). [ABSTRACT FROM AUTHOR]

• This study proposes a model to consider quality degradation in glass recycling. • The model is based on technical quality substitutability and market applicability. • The model was applied to a case study on glass waste treatment. • Accounting for quality degradation, only 83% of cullet can replaces raw materials. • The decrease of recycling benefits was of 13–23% for the examined impact categories. The sustainability assessment of waste management systems requires tools capable of evaluating material quality degradation during recycling. Existing research has predominantly focused on the development of substitutability models for plastics, leaving a gap in addressing other materials like glass. Glass is commonly regarded as endlessly recyclable, even though its actual recyclability depends on several crucial factors, such as colour and pollutant contamination. Many Life Cycle Assessment (LCA) studies in this field assume a one-to-one substitution coefficient, neglecting material deterioration and inaccurately representing real-world scenarios. This study proposes and assesses a substitutability model for glass, aiming to measure the replacement extent between virgin materials and recycled crushed glass (cullet). The methodology is based on two key factors: technical quality substitutability, considering impurities and colour contaminations in cullet, and market applicability, accounting for market demand. Once formulated, the model was applied to a European case study on glass waste treatment. Two scenarios were considered: one assuming complete substitution between cullet and raw materials, the other incorporating quality degradation. Findings indicate that, accounting for quality degradation, only 83% of cullet effectively replaces raw materials, resulting in a decrease of the benefit associated with recycling of 13–23% for the different examined impact categories, compared to complete replacement assumption. This underscores the importance of considering quality deterioration in glass recycling impact assessments. [ABSTRACT FROM AUTHOR]

Abstract Background Galla chinensis is a traditional Chinese medicine (TCM) produced due to the interaction between the Fordinae aphids and the Rhus plant species. Horned galls with high tannin content are the most widely cultivated gall type, and Wufeng county of Hubei province in China is the center of cultivation. However, long-term artificial cultivation and domestication of horned galls to meet the increasing production demand have led to quality degradation. Understanding the reasons underlying quality degradation is urgent for horned gall production and application. The present study used a combination of metabolic, genetic, and ecological analyses to investigate the quality and genetic differentiation of the horned galls under long-term domestication as well as the potential relationships between them. Results Analysis of gallic acid content and other three phenotypic traits (fresh weight, gall size, and wall thickness) revealed quality differentiation of horned galls collected from five locations in Wufeng, in which the cultivated samples from Wang Jiaping (WJP) showed the highest degradation. Genetic differentiation between the cultivated and wild Rhus chinensis trees in WJP, and between WJP and the other populations was detected based on SSR molecular markers, however, no significant difference in genetic structure was seen for the aphid populations. Among the various ecological factors examined, temperature was identified as the primary one affecting the quality of horned galls. Conclusions Both genetic and ecological factors caused quality differentiation of horned galls. The collection of diverse germplasm of host trees and aphids will help reduce the quality degradation of horned galls in Wufeng.

Peanut is an important oilseed crop, susceptible to quality deterioration under harsh storage conditions because of its high oil content. In order to explore the effects of different storage temperatures on peanut quality under normal humidity conditions, in-shell peanuts were stored at 15, 25 or 35 ℃ for up to 30 weeks. Indicators of lipid oxidation: acid value (AV), peroxide value (PV), and malondialdehyde (MDA) content; indicators of protein oxidation: carbonyl, sulfhydryl, disulfide bond contents; and the activities of oxidation-related enzymes: lipase (LPS), lipoxygenase (LOX) and peroxidase (POD) were tested. The results showed that the AV increased from (0.48 ± 0.01) to (1.78 ± 0.02) mg/g and the carbonyl content from (3.19 ± 0.24) to (118.61 ± 6.41) μmol/g over the storage period at 25 ℃. Meanwhile, at the end of storage, the highest lipase and lipoxygenase activities were observed in the sample stored at 35 ℃, which were (59.00 ± 1.70) and (1 287.17 ± 98.45) U/g, respectively; the AV increased from (0.48 ± 0.01) to (3.15 ± 0.10) mg/g, the MDA content from 23.03 to 1 039.63 nmol/g, and the carbonyl content from (3.19 ± 0.24) to (124.86 ± 3.07) μmol/g. At 15 ℃, the highest lipase and lipoxygenase activities were only (41.60 ± 1.23) and (1 036.14 ± 34.49) U/g, respectively and the peroxide and carbonyl contents increased by 18.4 and 17.1 times after 30 days of storage, respectively, reaching much lower levels than those at the other temperatures. In conclusion, storage at normal humidity and at 15 ℃ can effectively suppress the oxidase activity at a low level at all time points, resulting in a low degree of oxidation of peanut oil and protein, while high ambient temperature increases the oxidase activity, and the higher the temperature, the higher the enzyme activity, and the higher the contents of primary and secondary oxidation products in oil, indicating a higher degree of peroxidation. Moreover, protein oxidation also occurs due to the oxidation of amino acid side chains and protein structural damage, ultimately leading to a decline in peanut quality.

Managing degraded-quality materials in a supply chain with a single-vendor and multi- buyers is prevalent and critical in modern industry. This research addresses the single-vendor multi-buyer problem by incorporating multiple raw materials and quality degradation to maximize joint total profit (JTP). The proposed model utilizes the Whale Optimization Algorithm (WOA) for optimization, with empirical data derived from an agri-food industry case study in Indonesia. Experimental findings demonstrate the superior effectiveness of WOA compared to Chim optimization algorithm (ChOA), Genetic algorithm (GA), (GWO), Particle Swarm Optimization (PSO), and heuristic algorithm in solving the single-vendor multi-buyer problem. Sensitivity analysis reveals noteworthy insights: increased demand boosts total profit and production cycle efficiency, while elevated shipping costs for finished products negatively impact JTP by reducing production efficiency. Moreover, escalating quality degradation rates decrease JTP and production cycle time. This study significantly contributes to optimizing single-vendor and multi-buyer operations by addressing multiple raw materials and quality degradation, offering valuable insights into sensitivity analysis for critical factors in the agri-food industry.

Vacuum loss in packaged meats can lead to product defects resulting in significant economic losses and negative public health issues. Therefore, it is crucial to study the degradation of components that are critical for the provision of vacuum and package sealing to enhance system availability and process safety. Accordingly, this article proposes a condition‐based maintenance policy that integrates quality information considering meat cuts that lack proper vacuum as defective items. A deep reinforcement learning algorithm is used to learn a set of adequate maintenance actions to be performed at each maintenance inspection while maximizing the system availability and/or minimizing the total maintenance cost including the cost of producing defectives items. A numerical case study and benchmarking were performed, demonstrating that the proposed model surpasses the corrective maintenance policy. It leads to a 2.2% increase in system reliability, a 91% reduction in maintenance costs, a 93% reduction in defects identified in production, and a 90% reduction in defects identified on supermarket shelves. Such results demonstrate that the model can (i) prescribe maintenance actions at each inspection according to critical degradation states; (ii) exploit maintenance opportunities that lead to economic savings; and (iii) reduce product reprocessing and propagation of defects to shelves. Practical applications: A new machine learning‐based maintenance model promises to revolutionize the vacuum packaging industry by enhancing system reliability, reducing costs, and improving product quality. The model enables managers to make dynamic decisions based on the system state, avoiding inefficient maintenance planning and ensuring maximum productivity. By predicting quality performance through vacuum condition, the model allows for timely decision‐making and reduces the need for costly laboratory analysis. The free‐model's estimation of structural and economic relations of components enables managers to retrain and adapt maintenance policies for optimal system performance. With improved system reliability and reduced production of non‐conforming items, the industry can reduce reprocessing costs, contamination risks, and protect brand image by ensuring better control over meat hygiene. This new approach to maintenance optimization has significant implications for process safety, efficiency of operations, and profits of the vacuum packaging industry, making it a potential game‐changer in the field. [ABSTRACT FROM AUTHOR]

Background: Galla chinensis is a traditional Chinese medicine (TCM) produced due to the interaction between the Fordinae aphids and the Rhus plant species. Horned galls with high tannin content are the most widely cultivated gall type, and Wufeng county of Hubei province in China is the center of cultivation. However, long-term artificial cultivation and domestication of horned galls to meet the increasing production demand have led to quality degradation. Understanding the reasons underlying quality degradation is urgent for horned gall production and application. The present study used a combination of metabolic, genetic, and ecological analyses to investigate the quality and genetic differentiation of the horned galls under long-term domestication as well as the potential relationships between them. Results: Analysis of gallic acid content and other three phenotypic traits (fresh weight, gall size, and wall thickness) revealed quality differentiation of horned galls collected from five locations in Wufeng, in which the cultivated samples from Wang Jiaping (WJP) showed the highest degradation. Genetic differentiation between the cultivated and wild Rhus chinensis trees in WJP, and between WJP and the other populations was detected based on SSR molecular markers, however, no significant difference in genetic structure was seen for the aphid populations. Among the various ecological factors examined, temperature was identified as the primary one affecting the quality of horned galls. Conclusions: Both genetic and ecological factors caused quality differentiation of horned galls. The collection of diverse germplasm of host trees and aphids will help reduce the quality degradation of horned galls in Wufeng. [ABSTRACT FROM AUTHOR]

Copyright of Shipin Kexue/ Food Science is the property of Food Science Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Monitoring the quality degradation of shrimp during cold storage is a tough task due to the involvement of multi-biological process and the accurate kinetic model is extremely necessary to optimize the storage management. Here, the entropy weighting and global stability index (GSI) were combined to establish the model monitoring the shelf-life of Litopenaeus vannamei during storage at –23, –5, 0, 4 and 9 °C, respectively. The typically quality-related indicators including sensorial score, total aerobic count, total volatile base nitrogen, and activity of protease and polyphenol oxidase was selected to reflect the quality degradation. After systematical calculation, the weighting factors of these indicators were determined, respectively. Subsequently, the zero-order reaction model reflecting the overall quality degradation process was satisfactorily described based on GSI, in which the activation energy (Ea) and reaction rate constant (k0) were calculated to be (64.78 ± 0.75) kJ/mol and (3.47 ± 0.54) × 1011, respectively. As a consequence, the GSI model was established as following: GSI = 1 – 3.47 × 1011t × exp (–64.78 × 103/RT), with the relative error of less than 15%. Therefore, the established GSI model could be applied to monitor the quality deterioration of L. vannamei during cold storage and is helpful for distributors and consumers to determine the storing time.

The purpose of this review is to provide information on the nutritional value of mushrooms and how to preserve that quality after harvest. Mushrooms contain a variety of vitamins and minerals, including B, C, and D, and are low in calories and high in fiber (iron, phosphorus, copper, potassium and selenium). Consuming mushrooms may help prevent or treat serious health conditions like cancer, diabetes, and cardiac diseases. Mushrooms are high in protein and low in cholesterol. After being harvested, mushrooms' quality continues to deteriorate, showing signs of discoloration, moisture loss, texture changes, an increase in the number of microorganisms, and nutrient and flavor loss. Maintaining postharvest quality and extending the shelf life of mushrooms requires postharvest preservation techniques, such as physical, chemical, and thermal processes. To preserve its quality during post-harvest, there are a number of steps that must be taken, including precooling and refrigeration, washing with hydrogen peroxide, citric acid, sodium erythorbate, and calcium chloride, edible coating with Aloe vera, apple peel powder, carboxymethyl cellulose, lecithin, and tartaric acid, modified atmosphere packages, and use of high-quality packaging materials like polypropylene. Mushrooms can be kept fresher for longer by steeping and canning. Researchers, farmers, and academics interested in mushroom cultivation and its product diversification could benefit from this review.

A complete understanding of the potential environmental risks associated with carbon capture and storage (CCS) is critical for its large-scale deployment. Many experiments have simulated plant responses to soil CO2 stress caused by CCS leakage; however, crop quality has received less attention. This study assessed the effects of leaked CO2 from CCS on alfalfa yield and nutritional quality using pot experiments, focusing on crude protein and amino acids to address this knowledge gap. Our results showed that the aboveground and underground fresh weights decreased by 43.55 % and 66.06 %, respectively. The root-to-shoot ratio of alfalfa decreased from 1.04 to 0.63, indicating greater inhibition effects on the root than on the aboveground part of alfalfa. Crude protein and total amino acids in alfalfa declined by approximately 15.20 % and 11.37 %, respectively, compared to the non-leaked scenario. Our findings could potentially shed light on the environmental impact of CCS leakage, explicitly concerning the decline of crop quality, which adds to existing knowledge of the environmental effects of CCS failure.

Fish freshness can be considered as the combination of different nutritional and organoleptic attributes that rapidly deteriorate after fish capture, i.e., during processing (cutting, gutting, packaging), storage, transport, distribution, and retail. The rate at which this degradation occurs is affected by several stress variables such as temperature, water activity, or pH, among others. The food industry is aware that fish freshness is a key feature influencing consumers' willingness to pay for the product. Therefore, tools that allow rapid and reliable assessment and prediction of the attributes related to freshness are gaining relevance. The main objective of this work is to provide a comprehensive review of the mathematical models used to describe and predict the changes in the key quality indicators in fresh fish and shellfish during storage. The work also briefly describes such indicators, discusses the most relevant stress factors affecting the quality of fresh fish, and presents a bibliometric analysis of the results obtained from a systematic literature search on the subject. [ABSTRACT FROM AUTHOR]

This study presents a recurrent neural network (RNN)-based model for predicting physical quality changes in onions during long-term low-temperature storage. Unlike previous studies that primarily used simple regression equations with certain time points, this model utilizes time series-based storage-environment histories. The model was designed to use only easily obtainable, real-time environmental information and storage periods as inputs, thereby enhancing practicality. The onions were stored under controlled conditions for model development, with quality factor data accumulated through regular sampling and destructive testing. Data pre-processing addressed environmental noise and time resolution issues, and bioyield strength was selected as the prediction target considering interrelationships with environmental and quality factors. For comparison, four RNN-based models (stacked RNN, stacked long short-term memory (LSTM), residual LSTM, baseline LSTM) were proposed, along with a conventional multiple linear regression (MLR) model. Given the scarcity of preverified models for agricultural product quality prediction, a grid search was employed to explore various model structures and parameter combinations. The performance was compared using the same independent test data on the retrained models based on the optimized combinations. The residual LSTM model, scored 0.0532 on the normalized test root mean-squared error (RMSE), demonstrating the best performance by predicting up to 336 h ahead. The baseline LSTM model predicted up to 504 h with an RMSE of 0.0601. In contrast, the MLR model showed complete overfitting, with a test RMSE of 0.2814, indicating the unsuitability of utilizing storage history for quality prediction. This study verifies the potential of RNNs in agricultural product storage/distribution and anticipates the utility of the developed model as a foundational technology for future post-harvest process research. • Utilizing recurrent neural networks for predicting onion quality in cold storage. • Model designed on real-time environmental data for practical applications. • Proposed models recorded decent performance in both prediction accuracy and range. • Study highlights potential of RNNs in agricultural product storage and distribution. [ABSTRACT FROM AUTHOR]

• A single-manufacturer multi-retailer cold chain is investigated. • Quality degradation of the product occurs at multiple stages of the cold chain. • Quality degradation is captured by several features and the global stability index. • An algorithm is presented to determine the optimal solution. • It is found that operating a cold chain as a regular supply chain leads to a higher cost. This paper develops a model for a cold chain operated among a single product manufacturer and multiple retailers to minimize the total cost of the chain. A distinguishing feature of the cold chain is that the quality of the product degrades with time. The storage temperature and time influence the degradation rate. In this context, quality can be measured using multiple distinct indices. A global stability index is used to quantify the overall quality. The non-Arrhenius model is exclusively applied to measure the quality degradation during the transportation and at retailers' storage as the product moves in the cold chain. Optimal replenishment times for the manufacturer and retailers are decision variables and the cold chain's total cost includes the cooling cost, carbon emission cost, and loss of value in addition to the traditional supply chain costs. It is found that for a given manufacturer's replenishment time, the total cost is convex on each retailer's replenishment time. Hence, an algorithm is developed based on this property to find the optimal replenishment times for the manufacturer and retailers. This paper also investigates how specific cold chain parameters influence optimal decisions and the total cost. The analyses show that the resulting costs will be significantly higher if quality degradation is ignored in a cold chain. [ABSTRACT FROM AUTHOR]

Operational risk has been among the three most significant types of risks in the financial services industry, and its management is mandated by Basel II regulations. To inform better labor decisions, this paper studies how workload affects banks' operational risk event occurrence. To achieve this goal, we use a unique data set from a commercial bank in China that contains 1,441 operational risk events over 16 months. We find that workload has a U-shaped impact on operational risk error rate. More specifically, the error rate of operational risk events decreases first, as workload increases, and then increases. Furthermore, when workload is low, employees tend to make performance-seeking risks; however, when workload is high, employees tend to exhibit quality degradation due to cognitive multitasking. Based on the causal relationship between workload and operational risk events from the empirical analysis, we discuss staffing policies among branches aimed at reducing operational risk losses. We find that employing a flexible staffing rule can significantly reduce the number of operational risk events by 3.2%–10% under different scenarios. In addition, this significant performance improvement can be achieved by adding even a little bit of flexibility to the process by allowing employees to either switch their business lines in the same branch or switch branches within the same business lines on a quarterly basis. This paper was accepted by Vishal Gaur, operations management. [ABSTRACT FROM AUTHOR]

Copyright of Packaging & Food Machinery is the property of Packaging & Food Machinery Magazine and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Quality degradation due to inappropriate postharvest handling, including short exposure to high and variable temperature environments and cooling delay, is a critical issue for maintaining the freshness of vegetables and fruits in further marketing chains and final consumption. The goal of this research was to explore the influence of delayed cooling treatments on key quality attributes of tomatoes such as fresh weight, total soluble solids (TSS), firmness, and skin color (L*, a*, and a*/b*). Three treatments were applied to freshly harvested tomatoes: immediate storage (IS) after harvest, delayed cooling (DS) leaving tomatoes without cover for one day, and under cover (DSC) separately in a greenhouse and then storage in a controlled chamber at a temperature of 10 ± 1 ℃ and relative humidity of 90 ± 3%. The quality attributes of the stored tomatoes were examined for 15 storage days at 5-day intervals to examine the effects of cooling delay on the postharvest quality of tomatoes stored in a controlled chamber. After 15 days of storage, tomatoes that underwent the three treatments exhibited a progressive weight loss of 1.41%, 1.86%, and 1.69% for the IS, DS, and DSC treatments, respectively. Slower firmness reduction (31.2%) was observed for tomatoes with the IS treatment than for those with the other treatments over the storage duration. During the storage time, tomatoes that experienced the DS treatment exhibited higher increases in TSS (°Bx) values (4.79 to 5.76) than other tomato samples. Smaller changes in color values (L*, a*, and a*/b*) were observed for IS-treated tomatoes. During the storage time, overall changes were slower for IS-treated tomato samples than for those with other treatments. The results of this research indicate that the accumulation of field heat due to cooling delay could decrease the overall quality attributes of tomatoes in the market chain. The immediate transfer of harvested tomatoes to a cool temperature is strongly recommended.

Low-light image enhancement is a key technique to overcome the quality degradation of photos taken under challenging illumination conditions. Even though the significant progress has been made for enhancing the poor visibility, the intrinsic noise amplified in low-light areas still remains as an obstacle for further improvement in visual quality. In this paper, a novel and simple method for low-light image enhancement is proposed. Specifically, the subspace, which has an ability to separately reveal illumination and noise, is constructed from a group of similar image patches, so-called volume, at each pixel position. Based on the principal energy analysis onto this volume-based subspace, the illumination component is accurately inferred from a given image while the unnecessary noise is simultaneously suppressed. This leads to clearly unveiling the underlying structure in low-light areas without loss of details. Experimental results show the efficiency and robustness of the proposed method for low-light image enhancement compared to state-of-the-art methods.

Copyright of Shipin Kexue/ Food Science is the property of Food Science Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

[Display omitted] • We analyzed the freshness degradation of frozen Antarctic krill. • Non–targeted metabolomics analysis of physicochemical properties was used. • pH and water-holding capacity are potential indicators of quality deterioration. • Inosinic acid is a probable biomarker for umami degradation. This study aimed to determine the effect of different frozen temperatures during storage on the quality of Antarctic krill (Euphausia superba) and assess the change at the metabolite level via a combination of physicochemical property analysis, liquid chromatography–tandem mass spectrometry (LC–MS) based non–targeted metabolomics profiling. Regarding samples stored at –20 °C, the expressions of 7055 metabolites were elevated, while 2313 were downregulated. Lipids and lipid molecules had the highest proportion of differential metabolites. A total of 432 discriminatory metabolites with Kyoto Encyclopedia of Genes and Genomes (KEGG) IDs was obtained. We also observed that the concentrations of differential bitter free amino acids (FAAs) and oxidation products of arachidonic and linoleic acid increased. Moreover, as the storage temperature increased, the freshness, umami, and sweetness components were considerably reduced. Furthermore, results indicated that the color, pH and water–holding capacity (WHC) were potential indicators of quality deterioration, while inosinic acid was a probable biomarker for umami degradation of frozen Antarctic krill. In conclusion, this study demonstrates that storage at lower temperatures can be beneficial for maintaining the freshness of Antarctic krill from macro and micro perspectives. [ABSTRACT FROM AUTHOR]

The quality and shelf life of mushrooms are critical to their commercial viability. In this study, the effects of simulated transport vibration on postharvest quality of shiitake mushrooms (Lentinus edodes) were assessed over 12 days of storage. Furthermore, the protective performance of foam cushion material used in packaging during simulated transport was evaluated. Changes in respiration rate, weight loss, browning index, firmness, and malondialdehyde content were measured following vibration treatment. The results revealed that simulated transport vibration contributed to the deterioration of quality of shiitake mushrooms during storage, and the foam cushion material had a protective influence on the maintenance of shiitake mushroom quality. Taken together, our findings suggest that the foam cushion material used in packaging has the potential to improve the quality of shiitake mushrooms and extend their shelf life. [ABSTRACT FROM AUTHOR]

The northeastern slope of Mount Arjuno, Pasuruan district, East Java province, Indonesia represents a vast and good groundwater resource quality, generally be exploited by some companies for drinking water industries. Water unbalance and quality degradation is presumed to arise because groundwater extraction volume is getting bigger but less control by the regency authority. This study is to figure out the geologic condition and hydrogeological system, conduct groundwater exploitation risk assessment, and develop a conservation program. The study results show that the study area's geomorphological units can be divided into the volcanic summit, volcanic slope, fluvial plain, and anticlinal hills. The lithology comprises sandstone, breccia, and andesite lava of Mount Arjuno and Mount Welirang. The geological structures are anticline, normal fault, and lateral slip fault. Hydrologically, there are three watersheds, including Lumbangrejo, Ketanireng, and Prigen watersheds. The aquifers comprise unconfined to semi-confined aquifers with fissures and intergranular porosity. Based on risk assessment valuation, Pecalukan village of the Ketanireng watershed and Lumbangrejo village of the Lumbangrejo watershed are categorized as very high groundwater vulnerability zones, Karangrejo and Sukoreno villages of the Lumbangrejo watershed, Kedungringin, Kepulungan, and Gunungsari villages of the Ketanireng watershed are categorized as medium vulnerability zone. While, Ngorong village of the Lumbangrejo watershed, Gempeng, Oro-Ombo, Kalisat, and Dukuhsari villages of the Prigen watershed belong to the low vulnerability zone. The proposed conservation programs involve profitable water use safety campaigns, domestic waste, and industrial wastewater management, agricultural activities controlling, sandstone mining regulation, and reforestation. [ABSTRACT FROM AUTHOR]

Introduction: The water is the major key in sustainable development, so it is necessary to be managed and conserved. The quality of surface water resources is mainly controlled by natural or geogenic factors including chemistry of recharge water, soil and geology processes, as well as the man-made contaminant. Qualitative indicators are used as effective managing tools in decision making programs. Water quality indices (WQI) are the simple and suitable tools to determine the quality statue of the water. In order to calculate the water quality index, many parameters are integrated in mathematical formula to represent the quality condition of the water with a number which classifies the quality in the scales of the weak to excellent. Many water quality indices were introduced by researchers and organizations around the world. Aji-Chay, one of the most important flowing rivers in East-Azerbaijan province, northwest of Iran, is passing through Tabriz plain in its way and finally ends to the Uremia lake. Regarding the focused industrial zones, agricultural field and urban areas in this plain, the river is highly vulnerable to pollution and quality degradation. So, this study was aimed to assess the Aji-chay River based on quality indicators, in order to helps its better management. Materials and Methods: In this research for assessing pollution of the Aji-Chay river using water quality indices, 16 sampling stations were located along the river and water samples were collected during wet (May 2016) and dry (September 2016) seasons. Electrical conductivity (EC), temperature, dissolved oxygen (DO) and pH were measured in the field and total dissolved solids (TDS), turbidity, major ions (Ca, Mg, Na, K, HCO3, Cl, SO4), nitrate (NO3), phosphate (PO4), biological oxygen demand (BOD), chemical oxygen demand (COD) and biological contaminants (fecal coliform) were determined in the laboratory. Quality indicators including the US national sanitary foundation water quality indices in the two forms of multiplicative (NSFWQIm) and additive (NSFWQIa) and Iranian surface water quality index (IRWQIsc) were used to assess the quality of the Aji-Chay river. Results and Discussion: Turbidity and Electrical conductivity (EC) is high at the upstream which is related to movement of the River in upper red formation (Miocene series) which enhances the chloride, sodium, calcium and sulfate. Arsenic concentrations are exceeding the drinking standards (0.01 ppm) across all samples mainly from a geogenic sources as well as discharge of wastewater in some areas. The elements Cd, Mn, Ni, Pb, Mo, Co, Zn, Fe and Al are mainly geogenic, whereas Cu, Ba and Cr are mostly originated from anthropogenic activities. Based on the results, river quality at the wet season is highly controlled by the main branch and Gomnab-Chay, but Mehran-rood plays the major role in downstream water quality at the dry season due to its higher discharge rate. The process was confirmed by Piper and Schoeller diagrams. Most of the parameters are increased in middle parts at the river where the concentrated sources of contaminates and discharge of wastewater increased the organic and biological constituents and nutrients especially in dry season. Assessing the river quality for agricultural uses based on modified Wilcox diagram shows except for Mehran-rood, the other samples are unsuitable for agriculture and the dry season quality is better than the wet season. Based on the results, increase in most parameters and so, pollution and quality degradation of the river are observed to the downstream. Assessing quality of the Aji-Chay river using US national sanitary foundation water quality indices in the two forms of multiplicative (NSFWQIm) and additive (NSFWQIa) and Iranian surface water quality index (IRWQIsc) confirmed the bad to very bad qualitative statue of the river in most stations especially in the middle parts of the Tabriz plain. The results revealed that quality degradation of Aji-Chay river is probably due to discharge of contaminants from municipal and industrial wastewaters (effluents), highlighting the need for managing actions to improve quality of this important river. Comparing the quality indices showed the priority of NSFWQIm (multiplicative form of US national sanitary foundation water quality indices) in quality classification and pollution assessment of the Aji-Chay river. Conclusion: Quality degradation of Aji-Chay river is probably due to discharge of contaminants from municipal and industrial wastewater effluents, indicating the need for managing actions to improve quality of this river. In this study priority of NSFWQIm (multiplicative form of US national sanitary foundation water quality indices) in quality classification and pollution assessment of the Aji-Chay river was confirmed. [ABSTRACT FROM AUTHOR]

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Quality degradation due to inappropriate postharvest handling, including short exposure to high and variable temperature environments and cooling delay, is a critical issue for maintaining the freshness of vegetables and fruits in further marketing chains and final consumption. The goal of this research was to explore the influence of delayed cooling treatments on key quality attributes of tomatoes such as fresh weight, total soluble solids (TSS), firmness, and skin color (L*, a*,and a*/b*). Three treatments were applied to freshly harvested tomatoes: immediate storage (IS) after harvest, delayed cooling (DS) leaving tomatoes without cover for one day, and under cover (DSC) separately in a greenhouse and then storage in a controlled chamber at a temperature of 10 ± 1 ℃ and relative humidity of 90 ± 3%. The quality attributes of the stored tomatoes were examined for 15 storage days at 5-day intervals to examine the effects of cooling delay on the postharvest quality of tomatoes stored in a controlled chamber. After 15 days of storage, tomatoes that underwent the three treatments exhibited a progressive weight loss of 1.41%, 1.86%, and 1.69% for the IS, DS, and DSC treatments, respectively. Slower firmness reduction (31.2%) was observed for tomatoes with the IS treatment than for those with the other treatments over the storage duration. During the storage time, tomatoes that experienced the DS treatment exhibited higher increases in TSS (°Bx) values (4.79 to 5.76) than other tomato samples. Smaller changes in color values (L*, a*, and a*/b*) were observed for IS-treated tomatoes. During the storage time, overall changes were slower for IS-treated tomato samples than for those with other treatments. The results of this research indicate that the accumulation of field heat due to cooling delay could decrease the overall quality attributes of tomatoes in the market chain. The immediate transfer of harvested tomatoes to a cool temperature is strongly recommended. [ABSTRACT FROM AUTHOR]

To restore the degraded basketball video image, improve the adaptive tracking fusion ability of the image and improve the video information tracking ability of the degraded basketball video, we can accurately analyze the video image tracking curve of the degraded basketball video, so as to guide the basketball training. In this paper, a quality evaluation method of degraded basketball video image restoration based on classified learning and degraded basketball video information feature fitting capture is proposed. Firstly, the degraded basketball video image sequence is collected. The wavelet scale feature decomposition method is used to reduce the noise of the image, and then the gray pixel value feature point fitting capture of the degraded basketball video image sequence is carried out to realize the image quantitative analysis of basketball shooting trajectory. Finally, the simulation results show that the proposed method has high fitting degree and high precision of feature point extraction, which is of positive significance guiding basketball training. [ABSTRACT FROM AUTHOR]

• Summarized the intelligent detection technology of quality deterioration of fresh aquatic products. • Discussed the advantages and disadvantages of intelligent detection technology and the suggestions for the future development were put forward. • Summarized the non-thermal processing technology and natural preservatives to control the quality deterioration of fresh aquatic products. • The future development of intelligent detection and control technology for quality deterioration of fresh aquatic products. Fresh aquatic products are a popular and important food category. They are rich in nutrients, which can help improve the dietary structure and alleviate the problem of micronutrient deficiency. Fresh aquatic products are easily spoiled in the supply chain due to their quality characteristics, which not only leads to quality deterioration, but also may cause food safety problems. Throughout the supply chain of fresh aquatic products, it is crucial to identify and prevent quality decline. In order to adapt to the changing consumer demand, some new aquatic product quality detection technology and quality control methods are emerging. This article reviews several major categories of intelligent detection and quality control technologies, including spectral technology, sensory technology, non-thermal processing technology, and natural antiseptic. In this paper, the intelligent detection technologies and control methods of quality deterioration in the supply chain of fresh aquatic products are detailed reviewed from the aspects of principle, research progress and application along with an assessment of their development potential and application advantages and disadvantages. [ABSTRACT FROM AUTHOR]

We present a model to investigate the competitive implications of electronic secondary markets that promote concurrent selling of new and used goods on a supply chain. In secondary markets where suppliers cannot directly utilize used goods for practicing intertemporal price discrimination and where transaction costs of resales are negligible, the threat of cannibalization of new goods by used goods becomes significant. We examine conditions under which it is optimal for suppliers to operate in such markets, explaining why these markets may not always be detrimental for them. Intuitively, secondary markets provide an active outlet for some high-valuation consumers to sell their used goods. The potential for such resales leads to an increase in consumers' valuation for a new good, leading them to buy an additional new good. Given sufficient heterogeneity in consumers' affinity across multiple suppliers" products, the "market expansion effect" accruing from consumers' cross-product purchase affinity can mitigate the losses incurred by suppliers from the direct "cannibalization effect." We also highlight the strategic role that the used goods commission set by the retailer plays in determining profits for suppliers. We conclude the paper by empirically testing some implications of our model using a unique data set from the online book industry, which has a flourishing secondary market. [ABSTRACT FROM AUTHOR]

Recently, there are lots of visual tracking algorithms proposed to improve the performance of object tracking in video sequences with various real conditions, such as severe occlusion, complicated background, fast motion, and so on. In real visual tracking systems, there are various quality degradation occurring during video acquisition, transmission, and processing. However, most existing studies focus on improving the accuracy of visual tracking while ignoring the performance of tracking algorithms on video sequences with certain quality degradation. In this paper, we investigate the performance evaluation of existing visual tracking algorithms on video sequences with quality degradation. A quality-degraded video database for visual tracking (QDVD-VT), including the reference video sequences and their corresponding distorted versions, is constructed as the benchmarking for robustness analysis of visual tracking algorithms. Based on the constructed QDVD-VT, we propose a method for robustness measurement of visual tracking (RMVT) algorithms by accuracy rate and performance stability. The performance of ten existing visual tracking algorithms is evaluated by the proposed RMVT based on the built QDVD-VT. We provide the detailed analysis and discussion on the robustness analysis of different visual tracking algorithms on video sequences with quality degradation from different distortion types. To visualize the robustness of visual tracking algorithms well, we design a robustness pentagon to show the accuracy rate and performance stability of visual tracking algorithms. Our initial investigation shows that it is still challenging for effective object tracking for existing visual tracking algorithms on video sequences with quality degradation. There is much room for the performance improvement of existing tracking algorithms on video sequences with quality degradation in real applications.

Advances in image quality research have shown the benefits of modeling functional components of the human visual system in image quality metrics. Recently, visual saliency, an important aspect of the human visual system, is increasingly investigated in relation to visual quality perception. Existing studies have showed that incorporating visual saliency leads to improved performance of image quality metrics. However, current applications of visual saliency in image quality metrics mainly focus on the extension of a specific metric with a specific visual saliency model. Issues regarding the optimal use of visual saliency in image quality metrics remain. Psychophysical experiments conducted in the literature have revealed that visual artifacts occurring in an image can change fixation deployment relative to that of the image without distortion. As such, instead of using saliency models as add-ons to image quality metrics, we explored the approach of directly assessing image quality by measuring the visual saliency deviation triggered by visual artifacts. We first analyzed the relationship between visual saliency deviation and image quality degradation on the basis of a large-scale eye-tracking dataset. A saliency deviation-based image quality index was then devised. Experimental results showed that the proposed metric features high prediction accuracy and relatively low computational cost. • Visual quality degradation is linked and modelled with saliency deviation for the first time. • The proposed metric avoids ad-hoc saliency weighting and corresponding computational cost. • Both saliency and quality information of the test stimuli are provided. [ABSTRACT FROM AUTHOR]

Materials for recycling always contain a certain degree of contamination. The presence of impurities i.e. contamination in the recycling streams causes a change in the composition of the original materials to recycle. As a result, the quality of materials can be reduced in each successive step of recycling. In addition, the resources of lower quality are produced from the resource flows which had a higher quality in their original form. This kind losses of quality cannot be measured by mass balance, as well as the quality degradation not only can display measurements of mass. For the calculation of all losses caused by recycling contaminations, all further recycling processes required to return the materials back into resource cycles must be included. The method for calculating the exergy content and exergy losses of metal solutions during recovery and recycling is presented in this paper. The losses attributed to recycling, namely the material losses, the contamination losses with other metals, and the consequent need for dilution can be used as indicators of the quality loss of materials and of the efficiency of resource use in product systems. Therefore, exergy is proposed here as a measure of the efficiency of resources use. This paper presents calculations of exergy losses during recycling shown in the case of aluminum waste.

Background Agaricus bisporus is the mushroom with the highest global production yield. However, due to their natural unprotected structure, shelf-life of this kind of mushroom is quite short. During the postharvest period, mushroom experiences continuous quality degradation, presenting discolouration, moisture loss, texture changes, microbial count increasing, and nutrient and flavour loss. In order to maintain the postharvest quality and to extend the shelf-life of mushroom, postharvest preservation techniques including physical, chemical and thermal processes are essential. Scope and approach This review summarises quality degradation processes of mushrooms including moisture loss, discolouration, texture changes, microbial count increasing, and nutrients and flavour loss, analyses their influential factors including temperature, relative humidity, water activity, and respiration rate, and presents the preservation methods for mushrooms including drying, cooling, packaging, irradiation, washing, and coating. Key findings and conclusions The quality degradation process of mushrooms is complex, which is affected by both the inner factors related to mushroom itself and the outer factors related to storage conditions. For better preserving their postharvest quality, hybrid methods such as thermal techniques combined with physical or chemical techniques and novel non-thermal technologies including plasma, ultrasound and high pressure treatments are highly recommended. [ABSTRACT FROM AUTHOR]

In this paper, we present an accuracy-aware operating voltage management unit to improve the lifetime of processors by considering the error-resilient nature of some applications. This unit is placed in the power management unit of the processor and its operation is based on the aggressive operating voltage reduction during the runtime of error resilient applications. This unit determines the operating voltage of the processor based on the type of the running application, the predefined minimum acceptable quality, and the operating voltage level specified by the dynamic voltage frequency scaling controller of the processor power management unit. The determined operating voltage by this unit results in lifetime improvement and power reduction at the cost of timing violations that are tolerable by error-resilient applications. In addition, the proposed unit dynamically adjusts the minimum acceptable operating voltage based on the impact of aging mechanisms. The aging mechanisms considered in this work include Negative Bias Temperature Instability, Hot Carrier Injection, Time Dependent Dielectric Breakdown, Thermal Cycling, Electro-Migration, and Stress Migration. The efficacy of the proposed operating voltage management is investigated by applying it to some exact and error-resilient applications. The results show that the proposed unit lead to, on average, 38.82% lifetime improvement as well as 41.8% power consumption reduction. [ABSTRACT FROM AUTHOR]

[Display omitted] • Shrimp collagen was purified and its properties were studied. • Chewiness property of shrimp muscle showed a linear relationship with its collagen contents. • Shrimp collagen consisted of one α 1 chain and two α 2 chains with typical tripeptide sequences. • Serine proteinase from shrimp hepatopancreas played a critical role in collagen hydrolysis. Many factors are responsible for the diminished quality of shrimp during cold storage, while the role of collagen has rarely been studied. This study therefore investigated the relationship between collagen degradation and changes of textural properties of Pacific white shrimp, and its hydrolysis by endogenous proteinases. The textural properties of shrimp decreased gradually along with disruption of shrimp muscle tissues, and the chewiness property of shrimp muscle showed a linear relationship with collagen contents in muscle during 6-day-storage at 4 °C. Pepsin-solubilized collagen in shrimp muscle consisted of one α 1 chain and two α 2 chains, revealing a typical tripeptide sequence (i.e., Gly-X-Y) in their molecules. In addition, collagen could be hydrolyzed by crude endogenous proteinases extracted from shrimp hepatopancreas, and serine proteinase plays a critical role in the process. These findings strongly suggested that the quality reduction of shrimp during cold storage is closely associated with collagen degradation. [ABSTRACT FROM AUTHOR]

Lipid oxidation is among the major flaw-grounding processes in meat and meat-based products that can affect interactions among lipids and proteins, leading to critically undesirable changes. Therefore, it is imperative to control lipid oxidation in meat allied products to enhance consumer acceptability. Moreover, lipid oxidation is somber dilemma visage by the meat processing industry, affects food constituents, leading to detrimental alterations that can impart the deleterious effects on human health upon consumption. Various synthetic (butylated hydroxyanisole (BHA), butylated hydroxytoluene (BHT), and tertiary butylhydroquinone (TBHQ)) and natural antioxidants (vitamin C, vitamin A, tocopherols, especially vitamin E, flavonoids particularly quercetin, proteins, and peptides) as well as preservatives are employed to extend the storability of meat and resultants products; however, great consideration is paid to the utilization of natural antioxidants due to the harmful side effects imparted by synthetic counterparts. Recently, bioactive peptides are claimed to thwart lipid oxidation in meat and other products; in addition, these antioxidant peptides have also been reported to possess substantial health-promoting potential besides controlling oxidation. Therefore, the present review is intended to emphasize the sources, production methods, and applications of antioxidant proteins and peptides to control oxidative degradation in meat products and the potential health benefits of bioactive peptides. Furthermore, the techniques available for the extraction, characterization, and assessment of the antioxidant capability of bioactive peptides are discussed critically in this review. [ABSTRACT FROM AUTHOR]

Multistage manufacturing processes (MMPs) usually exhibit an interactive relationship between tool wear and product quality degradation. On one hand, the tool wear in a stage may result in the quality degradation of the products fabricated on that stage. On the other hand, the quality degradation at a preceding stage may lead to the change of the operational condition and thus affect the tool wear in subsequent stages. This interaction needs to be considered to accurately predict the residual life distribution (RLD) of MMPs, which will benefit condition-based maintenance and tool inventory management. In this paper, we propose an interaction model that utilizes a linear model to represent the impact of tool wear on quality degradation and a stochastic differential equation model to capture the impact of quality degradation on the instantaneous rate of tool wear. We then propose a Bayesian framework that incorporates real-time quality measurements to online update the RLD of MMPs. Our methodology is a generalization of an existing “QR-chain model,” which is dedicated into a similar research and application area. We conduct numerical studies to test the performance of our methodology and compare with the QR-chain model. The results show that our methodology outperforms the QR-chain model through capturing the impact of quality degradation on the process of tool wear and incorporating real-time quality measurements. [ABSTRACT FROM AUTHOR]

Salmonella Typhimurium 53647 was inoculated in eggs and inactivated with radio frequency (RF). Processing was conducted at 40.68 MHz, 35 W, 56.7 °C, and 19.5 min. Control and RF-treated eggs were stored at 7.2 °C and 10 °C, and the microbial counts and quality attributes (Haugh unit, weight loss, yolk and albumen pH, yolk index, and albumen turbidity) were assessed weekly for five weeks. Mathematical models were used to describe the growth of Salmonella and the quality degradation over time. The logistic, Gompertz, and Richards models accurately described the microbial growth in RF-treated eggs (R2 > 0.97). The weight loss was best described by zero-order kinetics and the Haugh unit by first-order kinetics. The Weibull equation described the behavior of albumen pH over storage. The degradation over time of the egg quality attributes was efficiently evaluated with the Global Stability Index (GSI). RF-treated eggs showed a better quality over time than control eggs based on the GSI values. • Logistic, Gompertz, and Richards models were used to describe Salmonella growth. • Quality degradation of eggs was fitted with zero – and first-order kinetic models. • GSI was successfully used to evaluate egg quality during storage. • RF-treated eggs showed better quality than control eggs during refrigerated storage. [ABSTRACT FROM AUTHOR]