This paper provides an overview of nondestructive imaging techniques for evaluating internal and external quality characteristics of fruits and vegetables and the future prospects of those technologies within the food industry. Low‐field nuclear magnetic resonance (LF‐NMR) and magnetic resonance imaging (MRI) are viable technologies in assessing water status, which can significantly impact the quality of fruits and vegetables' texture, tenderness, and microstructure. This review examined some of the most widely studied agricultural fruits and vegetables, described NMR/MRI techniques, and explained the benefits of their implementation in the assessment of internal quality attributes such as internal defects, water content, nutrition content, maturity, fruit firmness, and seed detection, as well as physicochemical and microbiological quality in both commercial and industrial applications. In spite of considerable developments in the quality measurement of fruits and vegetables and their products, the implementation of these techniques at an industrial level has been unsatisfactory. Practical applications This paper aimed to present a magnificent knowledge about fruit/vegetable processing and preservation techniques pertaining to quality evaluation. If the appropriate skills and the introduced tools are combined and utilized in an innovative and suitable way, a high quality of fruit/vegetable products with a high nutritional value can be achieved. This will be beneficial for both producers and customers.

No abstract

No abstract

Maritime transportation has a pivotal role in the foreign trade and hence, the world’s economic growth. It augments the realization of “Maritime Silk Road” strategy. However, the catastrophic nature of the maritime accidents has posed a serious threat to life, property, and environment. Maritime transportation safety is a complex system and is prone to human, equipment, and environment-based risks. In the existing literature, the risk assessment studies aimed at the analysis of maritime traffic safety usually consider the state of system as two ultimate states—one is the normal state and the other is the complete failure state. In contrast to the conventional approaches, this study incorporates a multistate criterion for system state giving consideration to the near or partial failures also. A Markov Chain-based methodology was adopted to determine the variations in state system and define the instant at which a low probability incident transforms into a high-risk intolerable event. The analysis imparts critical time nodes that could be utilized to reduce the risk and evade accidents. This study holds practical vitality for the concerned departments to circumvent the potential dangers and devise systematic preemptive procedures before the accident takes place. The results of this study could be employed to augment safety and sustainability of maritime traffic and decrease the associated pollution.

Seaports function as lifeline systems in maritime transportation, facilitating critical processes like shipping, distribution, and allied cargo handling. These diverse subsystems constitute the Port Infrastructure System (PIS) and have intricate functional interdependencies. The PIS is vulnerable to several external disruptions, and the impact of COVID-19 is severe and unprecedented in this domain. Therefore, this study proposes a novel general port safety framework to cope with recurring hazards and crisis events like COVID-19 and to augment PIS safety through a multi-state failure system. The PIS is divided into three critical subsystems: shipping, terminal, and distribution infrastructure, thereby capturing its functional interdependency and intricacy. A dynamic input–output model is employed, incorporating the spatial variability and average delay of the disruption, to determine the PIS resilience capacity under the stated disruptions. This study simulates three disruption scenarios and determines the functional failure capacity of the system by generating a functional change curve in Simulink. This study offers viable solutions to port managers, terminal operators, and concerned authorities in the efficient running of intricate interdependent processes and in devising efficient risk control measures to enhance overall PIS resilience and reliability. As part of future studies, given the difficulty in obtaining relevant data and the relatively limited validation of the current model, we aim to improve the accuracy and reliability of our model and enhance its practical applicability to real-world situations with data collected from a real-world case study of a PIS system.