The rise in the cost of essentials affects every nation around the world, but it has become a major concern for developing nations. It is getting increasingly difficult to keep up with rising prices for everyday items in these countries, where the majority of the population is from the middle class or lower middle class. Inflation, pandemics, wars, and other important variables all contribute to price increases. There may be another significant factor at play, which is supply-chain corruption. The supply chain\'s unreliable, chaotic, and opaque nature is to blame for this corruption. We are concentrating on the agri-food supply chain in our study. Because many of the current agri-food supply chains are intricate and challenging to monitor, dishonest parties can exploit the situation. Therefore, we suggested a thorough blockchain-based agri-food supply chain to identify the source of price increases. The private Ethereum blockchain was used in the suggested system. Since the private Ethereum blockchain is more efficient, safe, and fast, it was chosen. Smart contracts were created to describe the system and its underlying rules and laws. Furthermore, in order to showcase the usefulness of our smart contracts, we exhibited a sample decentralized application to support our hypothesis. We also gave the system a complete security and vulnerability assessment to make sure it is operating properly and is protected from threats and attacks. Due to the use of blockchain, the system is immutable, transparent, and simple to track and monitor. The proposed system has demonstrated greater transparency, traceability, reliability, speed, security, and cost-efficiency compared to conventional systems. It effectively traces the origin of corruption in the supply chain, providing a more straightforward means to tackle concerns related to price hikes.

Food systems rely on natural resources for production causing their depletion. Sustainability assessment can encourage farms and agri-food companies to improve sustainability performances. Sustainability assessment frameworks and tools differ in their purposes, scope, methods of application, and required time for execution; however, most of them do not fit with value chains, or they do not cover all sustainability dimensions. Our objective is to propose a holistic framework to assess sustainability at agri-food value chains level. The proposed framework combines the Sustainability Assessment of Food and Agriculture systems (SAFA) (El Hage, 2012) [1] and The Agri-food Evaluation Framework (TEEB) [2]. It incorporates the concepts of Socio-Ecological Systems, Assemblage, and Social Practices. It integrates system dynamics by emphasising human and natural capital stocks and their users. We explain in detail the methodological steps we followed to construct and to apply this new framework to two case studies in Italy and France. The new framework was applied to real-life case studies and has shown its effectiveness and demonstrates its potential for widespread use in similar scenarios.

The globalization of food markets has led companies to buy products not only locally, but also from other corners of the world. This has introduced complexity into supply chains, as products have to move longer distances and pass through more companies before reaching the end consumer. The meat industry has been no different. Events such as animal disease outbreaks have diminished consumer confidence in the industry and the supply chain. Coupled with this, consumers started demanding \"more transparent\" meat products. This has led companies to think about new traceability systems, which continue to enforce food safety and health rules, but at the same time enhance and make transparent to the consumer the origin and constitution of their products. This article proposes a traceability system in the agri-food (meat industry) with a multi-chain architecture, among them, blockchain. The use of blockchain in the traceability system helped to mitigate the omission of relevant data for the traceability process, allowing us to guarantee the immutability, reliability, and transparency of the data along the value chain. At the same time, the system was able to reduce the time of the traceability process by giving the user the possibility to access the traced information via a unique product identifier.

The present study aims to assess the impact of human activities on the water quality of the Hammam Boughrara dam. It also highlights the crucial importance of sustainable management of water resources in the face of persistent challenges related to various forms of pollution. The study is based on an exhaustive database covering a period spread over 16 years, with monthly measurements of organic pollution indicator parameters, namely BOD5, COD, [Formula: see text],[Formula: see text], [Formula: see text], [Formula: see text], Organic Matter (OM), TDS, Dissolved Oxygen (DO) and pH. The box plots showed an asymmetric distribution of almost all the parameters, with significant seasonal variations in the interquartile (IQR) range. The IQR ranges for [Formula: see text] extends from 0.575 mg/l (summer) to 4.445 mg/l (spring), and for [Formula: see text] from 1.3075 mg/l (autumn) to 1.8625 mg/l (spring). This led to the use of the Spearman method for the analysis of correlations between different parameters. The seasonal study of the five categories of water quality, according to the Organic Pollution Index (OPI), revealed considerable organic pollution. At the 1% significance level, the seasonal correlation between OPI and [Formula: see text] varies between -0.71 and -0.85, while that with [Formula: see text] fluctuates between -0.69 and -0.86. During the period analyzed, the COD/BOD Ratio (CBR) reveals two dominant categories with seasonal variations, i.e. the Moderately Biodegradable Effluents (MBE), with 96 cases, reaching 29 in autumn and 20 in spring. The Difficult to Biodegrade or Non-Biodegradable Effluents (DBE or NBE) category records 94 cases, with a maximum frequency of 26 in winter and minimum of 21 in autumn. These results therefore show the persistence of organic pollution, which had an impact on water quality over the four seasons and throughout the period studied. The results indicate persistent organic pollution affecting water quality. Therefore, prompt actions and sustainable strategies are deemed necessary to mitigate these harmful impacts and to ensure the sustainability of the water resource.

暂无摘要。

Tactile sensing plays a pivotal role in achieving precise physical manipulation tasks and extracting vital physical features. This comprehensive review paper presents an in-depth overview of the growing research on tactile-sensing technologies, encompassing state-of-the-art techniques, future prospects, and current limitations. The paper focuses on tactile hardware, algorithmic complexities, and the distinct features offered by each sensor. This paper has a special emphasis on agri-food manipulation and relevant tactile-sensing technologies. It highlights key areas in agri-food manipulation, including robotic harvesting, food item manipulation, and feature evaluation, such as fruit ripeness assessment, along with the emerging field of kitchen robotics. Through this interdisciplinary exploration, we aim to inspire researchers, engineers, and practitioners to harness the power of tactile-sensing technology for transformative advancements in agri-food robotics. By providing a comprehensive understanding of the current landscape and future prospects, this review paper serves as a valuable resource for driving progress in the field of tactile sensing and its application in agri-food systems.

A challenge in social marketing studies is the cognitive biases in consumers\' conscious and self-reported responses. To help address this concern, biometric techniques have been developed to obtain data from consumers\' implicit and non-verbal responses. A systematic literature review was conducted to explore biometric applications\' role in agri-food marketing to provide an integrated overview of this topic. A total of 55 original research articles and four review articles were identified, classified, and reviewed. It was found that there is a steady growth in the number of studies applying biometric approaches, with eye-tracking being the dominant method used to investigate consumers\' perceptions in the last decade. Most of the studies reviewed were conducted in Europe or the USA. Other biometric techniques used included facial expressions, heart rate, body temperature, and skin conductance. A wide range of scenarios concerning consumers\' purchase and consumption behaviour for agri-food products have been investigated using biometric-based techniques, indicating their broad applicability. Our findings suggest that biometric techniques are expanding for researchers in agri-food marketing, benefiting both academia and industry.

Currently, water scarcity affects more than three billion people. Nevertheless, the volume of treated wastewater discharged into the environment is estimated to exceed 100 m3 per inhabitant/year. These water resources are regularly used in agriculture worldwide to overcome water shortages. Such a practice, however, entails the uptake of waterborne pollutants, such as pharmaceuticals and personal care products (PPCPs), by crops and their further access to the food web, constituting an additional route of human exposure to PPCPs, with potential health outcomes. In this study, the occurrence of 56 PPCPs in tomatoes, lettuce, and carrot, together with soil and irrigation water, was evaluated using a QuEChERS-based methodology for extraction and LC-MS/MS for analysis. The influence of the selected cultivation conditions on the plant uptake levels of PPCPs was assessed. Two irrigation water qualities (secondary and tertiary treatment effluents), two soil compositions (sandy and clayey), two irrigation systems (dripping and sprinkling), and three crop types (lettuce, tomato, and carrot) were tested. Carrots showed the highest load of PPCPs (7787 ng/g dw), followed by tomatoes (1692 ng/g dw) and lettuces (1248 ng/g dw). The most translocated PPCPs were norfluoxetine (fluoxetine antidepressant main metabolite) (521 ng/g dw), and the anti-inflammatory diclofenac (360 ng/g dw). Nine PPCPs, are reported to be accumulated in crops for the first time. Water quality was the most important factor for reducing PPCPs\' plant uptake. Overall, the best conditions for reducing PPCP uptake by crops were irrigation with reclaimed water by sprinkling in soils with higher clay content. The risk assessment performed revealed that the crops\' consumption posed no risk to human health. This study serves as the first comprehensive assessment of the relevance of diverse cultivation factors on PPCPs\' plant uptake under field agricultural practices.

Interdisciplinary research needs innovation. As an action-oriented intervention, this Manifesto begins from the authors\' experiences as social scientists working within interdisciplinary science and technology collaborations in agriculture and food. We draw from these experiences to: 1) explain what social scientists contribute to interdisciplinary agri-food tech collaborations; (2) describe barriers to substantive and meaningful collaboration; and (3) propose ways to overcome these barriers. We encourage funding bodies to develop mechanisms that ensure funded projects respect the integrity of social science expertise and incorporate its insights. We also call for the integration of social scientific questions and methods in interdisciplinary projects from the outset, and for a genuine curiosity on the part of STEM and social science researchers alike about the knowledge and skills each of us has to offer. We contend that cultivating such integration and curiosity within interdisciplinary collaborations will make them more enriching for all researchers involved, and more likely to generate socially beneficial outcomes.

Anticipating and understanding fluctuations in the agri-food market is very important in order to implement policies that can assure fair prices and food availability. In this paper, we contribute to the understanding of this market by exploring its efficiency and whether the local Hurst exponent can help to anticipate its trend or not. We have analyzed the time series of the price for different agri-commodities and classified each day into persistent, anti-persistent, or white-noise. Next, we have studied the probability and speed to mean reversion for several rolling windows. We found that in general mean reversion is more probable and occurs faster during anti-persistent periods. In contrast, for most of the rolling windows we could not find a significant effect of persistence in mean reversion. Hence, we conclude that the Hurst exponent can help to anticipate the future trend and range of the expected prices in this market.