Product Quality Degradation Research Articles

Grafting of maleic anhydride onto waste acrylonitrile butadiene styrene (ABS) and its application for compatibilization of ABS blends

AbstractIncorporating recycled plastics into the manufacturing process is an essential way to establish a sustainable plastics economy. However, current processes are limited by the degradation of mechanical properties, high cost, and inconsistent product quality compared with their virgin counterparts. Here, we present an upcycling strategy for waste plastics where waste acrylonitrile‐butadiene‐styrene (reABS) is first grafted with maleic anhydride (MAH), then utilized to compatibilize nylon 6(PA6)/ABS and PA6/ABS/CaCO3 blends. The reABS‐g‐MAH exhibits improved Young's modulus and tensile strength, but lower strain at break and impact strength compared with reABS. As an additive, reABS‐g‐MAH effectively compatibilizes PA6/ABS and PA6/ABS/CaCO3 blends, indicated by greatly decreased PA6 domain size, homogeneous dispersion of fillers, and narrowed glass transition temperature regions between PA6 and ABS. Adding only 5 wt% reABS‐g‐MAH increases the Young's modulus, strain at break, and impact strength of PA6/ABS blends by 26%, 180%, and 110%, respectively, compared with uncompatibilized samples. Similarly, for PA6/ABS/CaCO3 blends, the strain at break and impact strength increase by 370% and 150%, respectively, while the Young's modulus and tensile strength show increases of 5% and 10%. The results show that this strategy of using polar groups to functionalize waste plastics as compatibilizers may open numerous opportunities for upcycling waste plastics.

Analysis and Verification on Buckling Mechanism of Spatial Tow Steering in Automated Fiber Placement

Automated fiber placement (AFP) enables the efficient and precise fabrication of complex-shaped aerospace composite structures with lightweight and high-performance properties. However, due to the excessive compression on the inner edge of the tow placed along the curved trajectory, the resulting defects represented by buckling and wrinkles in spatial tow steering can induce poor manufacturing accuracy and quality degradation of products. In this paper, a theoretical model of tow buckling based on the first-order shear deformation laminate theory, linear elastic adhesion interface and Hertz compaction contact theory is proposed to analyze the formation mechanism of the wrinkles and predict the formation of defects by solving the critical radius of the trajectory, and finite element analysis involving the cohesive zone modeling (CZM) is innovated to simulate the local buckling state of the steered tow in AFP. Additionally, numerical parametric studies and experimental results indicate that mechanical properties and geometric parameters of the prepreg, the curvature of the placement trajectory and critical process parameters have a significant impact on buckling formation, and optimization of process parameters can achieve effective suppression of placement defects. This research proposes a theoretical modeling method for tow buckling, and conducts in-depth research on defect formation and suppression methods based on finite element simulation and placement experiments.

Perceptron model application for traceability risk in spun pile manufacturing

A precise risk assessment in a production line constitutes a significant item to identify susceptible areas where there is a possibility of product quality degradation. This also applies to the precast concrete production line in Indonesia that has a spun pile product. Based on a risk assessment activity conducted in this study, it is proposed to build a traceability model in order to maintain and even improve the spun pile product quality in Indonesia. The approach used was the Neural Network of the perceptron model for weighing and will result in a defined traceability path in the context of reducing defects and even failed spun pile products. The simulation result showed that the model has been able to detect risky path possibilities to reduce product quality. The accumulation result of high-risk and medium-risk paths in this study showed that closer to product finalization, the risk will be higher. It is evident that when assessing Indicators, the order from the highest accumulation value first is Curing & Demolding and Stressing & Spinning at 29% each, Casting at 14%, Forming & Setting at 14%, and lastly Cutting & Heading at 14%. Regarding the risk assessment for activities, the first position is Curing & Demolding and Stressing & Spinning with 30% each, the second is Casting and Forming & Setting with 15% each, and the third is Cutting & Heading with 10%.

Root nutrition of plants: relevance, needs, problem solving

The article theoretically analyzes the nutrient needs of plants and the balanced supply of macro- and microelements for their proper growth and development. The basis of the research methodology is the systematic approach of assessing the periodicity of foliar feeding of plants with complex preparations of various compositions. It has been established that with foliar fertilization there is a part of nutrients after they enter the plant leaf. Smaller molecules or molecules with less positive charge are more easily transported in the vascular system, from where they move to other parts of the plant, including ammonium, potassium, and urea. On the other hand, larger molecules and ions with a large positive charge tend to stay fairly close to their point of entry because they stick to the negatively charged cell walls. They hold immobile nutrients quite tightly, including calcium, iron, manganese, zinc, and copper. The importance of the combination of biotechnological and ecological aspects in the development and application of complex compounds for foliar fertilization is indicated. The use of compounds based on EDTA is potentially dangerous for agricultural products and the environment. In the long term, this leads to increased pollution of agricultural land, soil degradation, reduced yield, and deterioration of product quality. When applying complex foliar fertilizers, elements with a strong positive charge, such as calcium, do not move very actively in the plant. Accordingly, negatively charged elements, such as phosphorus, slowly enter the leaves of plants. Both elements are relatively stationary after entry. Additional studies have shown that different plant species differ significantly in their ability to absorb nutrients through their leaves. Differences in cuticle thickness, number of pores, and resistance, as well as genetic and environmental factors, all affect a species’ ability to assimilate nutrients applied to leaves.

Improving Clothing Product Quality and Reducing Waste Based on Consumer Review Using RoBERTa and BERTopic Language Model

The disposability of clothing has emerged as a critical concern, precipitating waste accumulation due to product quality degradation. Such consequences exert significant pressure on resources and challenge sustainability efforts. In response, this research focuses on empowering clothing companies to elevate product excellence by harnessing consumer feedback. Beyond insights, this research extends to sustainability by providing suggestions on refining product quality by improving material handling, gradually mitigating waste production, and cultivating longevity, therefore decreasing discarded clothes. Managing a vast influx of diverse reviews necessitates sophisticated natural language processing (NLP) techniques. Our study introduces a Robustly optimized BERT Pretraining Approach (RoBERTa) model calibrated for multilabel classification and BERTopic for topic modeling. The model adeptly distills vital themes from consumer reviews, exhibiting astounding accuracy in projecting concerns across various dimensions of clothing quality. NLP’s potential lies in endowing companies with insights into consumer review, augmented by the BERTopic to facilitate immersive exploration of harvested review topics. This research presents a thorough case for integrating machine learning to foster sustainability and waste reduction. The contribution of this research is notable for its integration of RoBERTa and BERTopic in multilabel classification tasks and topic modeling in the fashion industry. The results indicate that the RoBERTa model exhibits remarkable performance, as demonstrated by its macro-averaged F1 score of 0.87 and micro-averaged F1 score of 0.87. Likewise, BERTopic achieves a coherence score of 0.67, meaning the model can form an insightful topic.

A deep reinforcement learning‐based maintenance optimization for vacuum packaging machines considering product quality degradation

AbstractVacuum 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 applicationsA 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.

Cold Chain Logistics Network Design for Fresh Agricultural Products with Government Subsidy

This paper investigates the cold chain logistics network design in the first mile for fresh agricultural products with government subsidy, involving the capacity, location of cold storage facilities, and transportation from production areas to cold storage facilities after harvest. A bi-level programming model is formulated considering the quality degradation of fresh agricultural products. Based on the proposition and KKT conditions, a solution method is designed for reformulating the bi-level model into a single-level programming model. Numerical experiments are conducted to verify the proposed model. Experimental results show that the solution method efficiently solves the problem of the cold chain logistics network design for fresh agricultural products with subsidy, and sensitivity analysis provides managerial insights for decision-makers.

EDUKASI PENANGANAN PASCAPANEN PRODUK HORTIKULTURA PADA PEDAGANG DI PASAR TRADISIONAL BLAMBANGAN

Postharvest losses in horticultural products reach 45-55%, the main cause of postharvest losses in fruit and vegetables is caused by the product losing water due to respiration and transpiration processes which reduce product weight. Until now, Indonesia still contributes a very large postharvest loss, this is due to the lack of awareness and knowledge from both farmers, traders, and consumers regarding good postharvest handling. Most of the post-harvest losses occur during the marketing process, and this is what makes traders suffer a lot of losses. Therefore, educational activities are needed for post-harvest handling of horticulture products to prevent these losses, especially in the Blambangan Banyuwangi Market. Post-harvest handling that can be carried out by traders to prevent quality degradation of horticultural products includes sorting, trimming, grading, modifying packaging, and modifying storage. Educational activities for post-harvest handling of horticultural products for traders in the Blambangan traditional market run enthusiastically and can be declared successful. All participants can understand the entire material presented, not only that the participants are also able to implement the material directly starting from the process of sorting, trimming, and grading the products they sell. Participants were also able to apply packaging technology starting from selecting the appropriate type of packaging plastic and also making perforated holes in the plastic to reduce the rate of respiration so that fruit and vegetable products sold have a longer shelf life.

Analysis of the raw material base for pectin production

The addition of pectin to food products is important because this natural polysaccharide plays a key role in improving the quality and stability of the product, it allows for high-quality preservation of products that have a long shelf life, which is important for the health and wellbeing of consumers. The purpose of the study is to investigate the main raw materials of plant origin for the synthesis of pectin, which can be used as a promising raw material for food industry enterprises in Ukraine. The study was carried out using various methods of analysis, a thorough comparative analysis of papers by Ukrainian and foreign researchers, which are published in the scientometric databases Scopus, Web of Science, Journal Citation Reports, Scimago Journal & Country Rank, and Google Scholar. Based on the results of analytical studies, the main raw materials used for the production of pectin and pectin-containing pastes were analysed, and the main problems of the production process were identified. It has been found that adding pectin to food products can have a significant number of benefits: increasing the viscosity of the product, which is useful for creating a thick texture of the product; increasing the resistance of the product to heat treatment, reducing the risk of product separation or quality degradation; increasing functionality; introducing it into products can help improve the consistency and appearance of the product, add taste and color properties, and reduce the amount of sugar that must be added to the product to ensure viscosity and taste. It is established that the main raw material for the production of pectin in Ukraine is apple fruits. It is proven that pectin can be obtained from other fruits, berries, and vegetables, such as gooseberries, currants, cherries, pumpkins, etc. The intensification of the pectin production process should provide the population with a high-quality product that will prevent various types of intoxication by removing radionuclides from the body and contribute to the recovery of people in the post-war period. The practical significance of this study lies in the ability to help manufacturers find optimal sources of raw materials with a high pectin content to ensure the quality of the final product. In addition, this study will also facilitate the development of appropriate technological solutions for the optimal process of producing pectin from the selected raw materials

Combustion and Stubble Burning: A Major Concern for the Environment and Human Health

Combustion is an essential process for humanity, but it has created turbulence in society due to the pollutant emissions from the partial completion of its process and its byproducts. The regular population is unaware of the repercussions being faced in terms of health deterioration, product quality degradation, biodiversity loss, and environmental harm. Although strategic planning against the effects is being applied sideways by the authorities to the local population and industrial facilities, the awareness in the local population is still minimal. The indicators for bioremediation being required, observed through increased sales of pharmaceutical medicines and supplements, air filters, and new techniques, include smog, elevation in respiratory disease, health immune system deterioration, decreasing life span, increasing mortality rate, and degradation in the food and water quality. This article gives a brief overview of the problems being faced due to uncontrolled combustion activities, the sources of pollutants, their creation, emission, and dispersal process, along with the mitigation techniques developed to overcome the after-effects on human health and environment.

Individual and interactive effect of ultrasound pre-treatment on drying kinetics and biochemical qualities of food: A critical review.

One of the earliest and most prevalent processing methods to increase the shelf-life of foods is drying. In recent years, there has been an increased demand to improve product quality while lowering processing times, expenses, and energy usage in the drying process. Pre-treatments are therefore effectively used before drying to enhance heat and mass transfer, increase drying efficiency, and lessen degradation of final product quality. When food is dried, changes are expected in its taste, color, texture, and physical, chemical, and microbial properties. This has led to the need for research and development into the creation of new and effective pre-treatment technologies including high-pressure processing, pulsed electric field, ultraviolet irradiation, and ultrasound. Sound waves that have a frequency >20kHz, which is above the upper limit of the audible frequency range, are referred to as "ultrasound". Ultrasonication (US) is a non-thermal technology, that has mechanical, cavitational, and sponge effects on food materials. Ultrasound pre-treatment enhances the drying characteristics by producing microchannels in the food tissue, facilitating internal moisture diffusion in the finished product, and lowering the barrier to water migration. The goal of ultrasound pre-treatment is to save processing time, conserve energy, and enhance the quality, safety, and shelf-life of food products. This study presents a comprehensive overview of the fundamentals of ultrasound, its mechanism, and how the individual effects of ultrasonic pre-treatment and the interactive effects of ultrasound-assisted technologies affect the drying kinetics, bioactive components, color, textural, and sensory qualities of food. The difficulties that can arise when using ultrasound technology as a drying pretreatment approach, such as inadequate management of heat, the employment of ultrasound at a limited frequency, and the generation of free radicals, have also been explained.

Fuzzy Production Inventory Model considering Imperfect Quality and Shortage: A Case Study in a Goat Milk SMEs

Goat milk powder is one of the perishable processed products. The decreasing quality of goat milk powder can cause financial losses to the company if not regulated properly. So far, the company is also faced with the problem of consumer demand uncertainty. When demand for powdered goat's milk is high, the company experiences stockout but can be overcome by backorder. When demand is low, there will be overstock. Overstock conditions, in addition to causing high holding costs, are also at risk of product quality degradation or expiration. In this study, an inventory model of goat milk powder was developed that considers the uncertainty of demand, product quality, and backorder to determine the optimal production quantity so that the total inventory cost incurred is minimum. The basic model used is economic production quantity. Uncertainty in demand and the percentage of products declining in quality is approached using a triangular fuzzy. While the defuzzification technique used is signed distance.

Novel rapid cooling system design and modeling for continuous flow food processing systems

The commercial sterility in thermal processing is achieved by implementation of high temperatures that often has a negative impact on the heat sensitive health promoting nutrients like vitamins, antioxidants, flavors, and phytochemicals. Although tremendous progress has been made in rapid heating with the advancements in volumetric heating technologies like ohmic and microwave heating, the advancement in rapid cooling remains unexplored to further minimize the product quality degradation. A novel rapid cooling heat exchanger design modification was made to the traditional cooling system to improve the rate of cooling by direct injection of cooling gas media. Pilot-scale tests were conducted on a model food with an Ultra High Temperature (UHT) processing unit and an add-on novel cooling design. The cooling rate achieved by the rapid cooling design was found to be 7.5 ± 0.01 °C/s, which was 15 times the cooling rate provided by the traditional UHT cooling system. Mathematical models were developed to predict the time-temperature profile and the nutrient retention based on the new design. The model simulations for the new cooling design showed additional retention of 14.81% antioxidant content, 4.13% anthocyanins, 14.43% total flavonoid content as compared to the traditional cooling system.

Recent advances in ultrasound‐coupled drying for improving the quality of fruits and vegetables: a review

SummaryDrying is a commonly used fresh‐keeping technology. Conventional drying technologies such as convective drying, freeze‐drying causes the degradation of product quality due partly to long drying time. Ultrasound as a great potential technology is applied to improve drying process of fruits and vegetables. This review provides recent advances in ultrasound‐coupled drying for improving the quality of fruits and vegetables. Effects of ultrasound‐coupled drying were stated in detail. The designs of ultrasound‐coupled drying systems were described, indicating that these systems effectively reduced drying time. Effect of ultrasound‐coupled drying on the quality of fruits and vegetables was reviewed. Ultrasound‐coupled drying was helpful to improve physicochemical quality attributes such as colour, water activity, texture, rehydration capacity, bioactive compounds, antioxidant capacity, microstructure and shelf life of fruits and vegetables. Hence, this suggested that ultrasound application is a promising technology to improve drying process of fruits and vegetables.

A method for automatic real-time detection and counting of fruit fly pests in orchards by trap bottles via convolutional neural network with attention mechanism added

Fruit fly pests seriously affect the quality and safety of various melons, fruits, and vegetable crops. Many farmers lack sufficient knowledge of the level of pest occurrence, which leads to the over-use of pesticides, resulting in environmental pollution and quality degradation of agricultural products. The combination of artificial intelligence and agricultural technology can continuously and dynamically monitor pests in orchards, help scientific researchers and fruit farmers master pest data in time, reduce the use of artificial and pesticides, and achieve scientific early warning and prevention of pests. In this paper, the sexual attractant is placed in the pest trap bottle, the optical flow method, U-Net semantic segmentation, and the YOLOv5 algorithm with SE, CBAM, CA, and ECA attention mechanisms are used to detect and count live Bactrocera cucurbitae on the bottle surface, and then we use Hough circle detection method to detect the entrance position of the trap bottle, and finally count the number of B. cucurbitae entering the trap bottle in combination with the position information of B. cucurbitae and the entrance of the trap bottle. The experimental results show that: the accuracy of counting B. cucurbitae on the surface of the trap bottle can reach 93.5%, and the accuracy of counting B. cucurbitae entering the trap bottle can reach 94.3%, which can dynamically monitor the number of pests in the orchard in real time.

Shelf Life of Combination Nori Sargassum sp. and Eucheuma spinosum with Alumunium Foil Packaging Based on the Accelerated Shelf Life Test Method

The purpose of this research was to determine the shelf life of Combination Nori Sargassum sp. and Eucheuma spinosum with the Accelerated Shelf Life Test (ASLT) method Arrhenius Model using Alumunium Foil packaging. This research was conducted at the Laboratory of Fisheries Product Processing, Faculty of Fisheries and Marine Sciences, Padjadjaran University from October to November 2020. Sargassum sp. is a genus of brown algae (Phaeophyta) used as in the food industry and non-food industry. Sargassum sp. cannot form nori sushi sheets because it lack carageenan. Eucheuma spinosum is a genus of red algae (Rhodophyta) used to complement the lack of carageenan in Sargassum sp. Alumunium foil is a metalized plastic package composed of hermetic, flexible and opaque metal that has high protection againts light, water vapor and gas. The determination of the shelf life of the ASLT method is carried out using parameters of environmental conditions that can accelerate the product quality degradation by storing the product at high risk temperature. The observation used in determining the shelf life of Combination Nori Sargassum sp. and Eucheuma spinosum is a sensory test and water content test with 35 days in the storage at a temperature of 25oC and 35oC. The calculation results of the Arrhenius model used texture parameter as critical parameters that had the lowest Activation energy (Ea) in determining the shelf life of combination nori which packaged with alumunium foil. The results showed the value of texture parameters based on the order 0 reaction with the Arrhenius plot Ln K = -2.8019, 1/T = 97.596 and Ea = 193.92. The shelf life of combination nori Sargassum sp. and Eucheuma spinosum that stored at room temperature (25oC) was around 137 days.

Application of vibration analysis using time-frequency analysis to detect and predict mechanical failure during the nut manufacturing process

The nut manufacturing machine operates almost continuously throughout the day and, consequently, requires frequent maintenance, the duration of which depends on the type of fault. Unpredicted downtime can cause loss of production volume, inability to meet critical timelines, and product quality degradation. Vibration research was conducted on a six-die nut manufacturing machine, which experienced frequent faults on the fourth and sixth dies that exerted the greatest impact on the nut material. The application of several analytical techniques on vibration data – the fast Fourier Transform, Empirical Mode Decomposition, Multiscale Entropy, Shock Response Spectrum, and correlation – enabled the identification of fault indicators, which would be useful for predictive maintenance. These features were detectable up to 8 h 28 min and up to 1 h 9 min prior to failure or deterioration resulting from severe and regular damage, respectively. Faults included quality deterioration and die and non-die breakage, fusion, bending and cracking. This research can optimise machine efficiency through timely upkeep facilitated by predictive maintenance.

Quality Risk Management in Infusation Product Distribution Using Failure Mode and Effect Analysis (FMEA) and Analytical Hierarchy Process (AHP) Methods

This study aims to determine the causes of product leaks so as to minimize the risks of product quality degradation. The research method used is descriptive qualitative research method, data collection techniques used are observation, interviews and documentation. The collected data is then analyzed to obtain useful information to solve a problem in research. The process of testing the validity and reliability in this study uses a triangulation process. In this study, to measure Quality Risk Management, FMEA is used as a tool to measure or identify the source or cause of a quality problem. The next method to solve problems or risks in Quality Risk Management is AHP. The results of the study can be concluded that, Quality Risk Management in the distribution of Infusion products. The risk with the highest RPN value is the risk of damaged goods in the distribution flow of releasing goods from the warehouse to the expedition of PT. BSP which causes a leak in the softbag packaging. These risks are then analyzed to find the best alternative for handling them. Determine alternative handling of Quality Risk Management in the distribution of Infusion products at PT. BSP using the AHP method. Based on calculations using Expert Choice 11 software, the priority criteria are time and handling effectiveness which has the highest pairwise comparison value is the alternative of adding product handling information labels on cardboard packaging.

Warna, Kadar Air, Kadar TBA, dan Aktivitas Antioksidan Sup Jangkang (Jagung-Cangkang) Instan Dengan Perbedaan Teknik Kemasan Dan Lama Penyimpanan

Instant corn soup is included in the dry form of flour products that have the ability to easily absorb water from the environment (high hygroscopic). Water vapor transfer from the environment can cause quality degradation during storage. The decline in quality triggers chemical, enzymatic or physical reactions to changes in sensory properties. Packaging is known to be able to minimize product quality degradation. The packaging technique can be done by vacuum and non-vacuum techniques. The general objective of the study was to determine the effect of packaging techniques and storage time on the physical and chemical characteristics of instant corn soup enriched with duck eggshell flour. The experimental research method uses factorial completely randomized design (CRD), which consists of 2 factors 8 treatments, namely metallized (vacuum and non vacuum) packaging techniques and storage time (1, 2, 3, and 4 weeks). Each treatment was repeated 4 times, so that 32 units of the experiment were obtained. Data on the results of physical characteristics and chemical characteristics were analyzed using ANOVA statistical methods followed by DMRT advanced tests. The results showed there was an effect of packaging technique and storage time on TBA levels and antioxidant activity, but there was no effect on the color and water content of instant corn soup. Metallized vacuum packaging with 3 weeks storage produced color (13.56%), water content (5.72%), TBA content (0.52 mg MA / kg sample), and antioxidant activity (8,94% RSA).

Strategic rationing and freshness keeping of perishable products under transportation disruptions and demand learning

This paper considers a retailer who sells perishable fresh products directly to customers through an online channel and encounters a transportation disruption. Products shipped during the disruption period come with an uncontrollable delivery lead time, resulting in product quality degradation. To balance the compensation price provided to customers because of quality losses, the retailer might employ freshness-keeping efforts to reduce the quality loss during transportation. Therefore, it raises several fundamental questions for the retailer in mitigating the disruption. Is it always optimal to satisfy those customers who are willing to purchase during disruption? If it is profitable to fulfill orders along with an extra delivery lead time, and with a quality loss compensation, what is the optimal freshness-keeping effort? If it is preferable to deliberately create unsatisfied demand by announcing shortages (rationing) to customers, when is the optimal time to do so? To answer these questions, we first present the dynamics of post-disruption inventory and demand, taking into account the demand learning effect facilitated from negative word-of-mouth during disruption and the demand recovery after disruption ends. Afterward, we develop a model to achieve the optimal selling strategy for maximizing post-disruption profit, identifying the joint decision of the rationing period and freshness-keeping effort. Finally, by numerical analysis, three types of selling strategies are visually provided to hedge against disruptions of different lengths.