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Food Security and Its Impact on Society: Cases of Developing World
Food security is a matter of concern in the twenty-first century as is evident from the importance given to it in the United Nations Sustainable Development Goals. Despite attempts to address food scarcity concerns at global conventions such as the World Food Summit of 1996, food remains scarce. Scholars further suggest that though food scarcity is a global issue, its roots and impact is local. Consequently, a study of food must study the major challenges that converge to undermine food security worldwide including conflicts, climate change, global policies and in recent times even the Covid 19 pandemic. However, at a fundamental level food scarcity is the by-product of not just a legacy of past failures to build more just, sustainable, and resilient food systems, but rather a by-product of our inability to be responsible and sustainable consumers. This chapter highlights that despite surplus food production, developing nations often face food insecurity owing to the diversion of food towards developed nations. These nations, instead of sharing global resources (including food and agricultural labour), often contribute towards the global food crisis. Moreover, some of these developed nations engage in an industrialised system of food produc-tion which might meet the nations food requirements but are not sustainable modes of production and pose a serious threat to the environment. Nevertheless, the indis-cretions of the developed nations affect the developing nations economically as well as socially. As social outcasts, marginalised communities and individuals within the developing world are worst affected. As a result, this chapter offers insight into the social struggle brought on by inaccessibility to food. The chapter further suggests that addressing concerns of food security is not only a matter of addressing the inequalities manifest in the production, distribution and consumption of food but also learning to be responsible and sustainable consumers. Simply stated, the chapter recommends connecting SDG 2 with SDG 12. This chapter would also include the position of India in GHI, the Ukraine crisis and its aftermath in various developing countries, the earthquake in Turkey and how it affects the food security, and a few instances from Africa to highlight the concepts of food security and its correlation with sustainability of any society. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Food Security and Global Institutions: A Global Justice Perspective
Food security refers to a condition where all people have physical and economic access, at all times, to sufficient, safe and nutritious food that meets their needs and food preferences to lead an active and healthy life. Universal Declaration of Human Rights, 1948 (UDHR) declares the right to food as a basic human rights. International Covenant on Economic, Social and Cultural Rights, 1976 (ICESR) explicitly recognises the right of everyone to food and mandates all state parties for its realization; also it recognizes everyones right to be free from hunger as a fundamental right. Further, it instructs the state parties to ensure equitable distribution of world food supplies to achieve the right of everyone to be free from hunger. Rome Declaration on World Food Security, 1996 reaffirmed the right of everyone to access to safe and nutritious food compatible with right to adequate food and also right to be free from hunger. United Nations Millennium Declaration set the goal for fighting hunger and resolved to reduce the proportion of people suffering from hunger to half by 2015, then Sustainable Development Goals were floated, inter alia, to end extreme poverty and achieve the target of zero hunger and food security by 2030. Regardless of its being a universal human rights, food security scenario across the globe is far from satisfactory and fair. Post COVID 19 scenario has seen a surge in undernourishment and food insecurity. According to The State of Food Security and Nutrition in the World, 2022, 3.1 billion people across the globe are unable to afford a healthy diet. At this juncture we are living in a deeply connected and globalized world run not by national institutions but by global institutions. The role of global institutions assume significance in a globalized world. Justice demands that policy planning and legal framework on food security should be fair and equitable; they should be based on the idea of entitlement and obligation. To achieve the goal of zero hunger and food security, what is required is an equitable and unified global governance approach premised upon the idea of global justice which shall fix obligations on global institutions. This chapter aims at examining the issue of food security from a global justice perspective and how it can be sustainably achieved. It will explain the concept of global justice and obligations of global institutions by relying upon few legal and political theories. Further, the chapter will explain the human rights perspective of the food security and the challenges involved with it. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Food Recommendation System using Custom NER and Sentimental Analysis
In today's fast-paced lifestyle, the need for efficient and personalized solutions is paramount, especially in the category of dining experiences. This research responds to this demand by proposing a better food recommendation system for Zomato reviews. It targets the audience who are not aware of the best cuisines and search for user reviews online. Utilizing custom Named Entity Recognition (NER) and sentiment analysis, the system seeks to understand and cater to individual food preferences extracted from user Reviews. Specifically, improving the analysis by extracting reviews for ten restaurants in the city of Kolkata. By providing a specific solution to address the current research gap in the area of restaurants recommendation systems, the system recommends top choices for neighboring restaurants and best food based on the sentimental analysis of the chosen menu items. 2024 IEEE. -
Food quality traceability prototype for restaurants using blockchain and food quality data index
As competition between organizations are evolving into competition between supply chains, to survive and indeed grow, it is necessary to deliver added value to customers. Traceability has emerged as one of the key measures of operational efficiencies within supply chains and ultimately, customer service. Over the years, organizations have deployed number of methods in delivering food traceability. This paper examines major methods of food traceability currently in existence and proposes a restaurant prototype for implementing more reliable food traceability using Blockchain and product identifiers. The prototype captures data from various stakeholders across the food supply chain, segregates it and finally, applies the Food Quality Index (FQI) algorithm to generate an FQI value. The FQI value helps in identifying whether the food is good for consumption on specified parameters. FQI value is generated based on extant standard storage and handling regulations specified by food safety authorities, and checks whether value so derived, is within the permissible range. The prototype helps in grading food quality for human consumption besides strengthening food (product) traceability. This prototype can be customized to address future requirements of traceability triggered through new information emanating from any stakeholder or the node in the supply chain. 2019 Elsevier Ltd -
Food Quality Indicator-Based Intelligent Food Packaging
Foodborne illnesses caused by microbial growth and consumption of spoiled food items can lead to severe health issues. Monitoring real-time food quality through indicators/sensors has been an important priority for food industries, researchers, consumers, and regulatory bodies in this context. Intelligent packaging (IP), a type of food packaging, uses an indicator component to track and alert consumers on the quality of packaged food from the stage of manufacture to consumption in real time. Intelligent packaging helps reduce food waste and ensure consumer safety. This book chapter will discuss various food quality indicators, including humidity, oxygen, carbon dioxide, pH, and microbial indicators, and their applications in IP. 2025 John Wiley & Sons Ltd. All rights reserved. -
Food innovation adoption and organic food consumerism-a cross national study between Malaysia and Hungary
In order to meet the rising global demand for food and to ensure food security in line with the United Nations Sustainable Development Goal 2, technological advances have been introduced in the food production industry. The organic food industry has benefitted from advances in food technology and innovation. However, there remains skepticism regarding organic foods on the part of consumers, specifically on consumers acceptance of food innovation technologies used in the production of organic foods. This study measured factors that influence consumers food innovation adoption and subsequently their intention to purchase organic foods. We compared the organic foods purchase behavior of Malaysian and Hungarian consumers to examine differences between Asian and European consumers. The findings show food innovation adoption as the most crucial predictor for the intention to purchase organic foods in Hungary, while social lifestyle factor was the most influential in Malaysia. Other factors such as environmental concerns and health consciousness were also examined in relation to food innovation adoption and organic food consumerism. This paper discusses differences between European and Asian organic foods consumers and provides recommendations for stakeholders. 2021 by the authors. Licensee MDPI, Basel, Switzerland. -
Food Detection and Recognition Using Deep Learning - A Review
Studies show poor lifestyle choices and unhealthy eating patterns cause issues like obesity and other ongoing illnesses that raise the risk of heart attacks, such as hypertension, abnormal blood sugar levels, and diabetes. To improve this situation a lot of health apps have been built which use modern dietary monitoring systems that automatically evaluate dietary intake using machine learning and deep learning techniques rather. For these reasons indepth investigations on food detection, classification, and analysis have been conducted. Some of the top methods for automatic food recognition created have been discussed in this paper. We also propose an idea for detection of Indian food items using image classification. According to our findings of the papers we reviewed, convolutional neural networks (CNN) have been extensively been used in food detection as it has been giving better results compared to other models. We also observed that Vision transformers perform better in situations where the dataset is large and a hybrid model would give better accuracy. A review of potential applications for food image analysis, shortfalls in the area, and open issues concludes the paper. 2022 IEEE. -
Food calorie estimation using convolutional neural network
The modern world healthy body depends on the number of calories consumed, hence monitoring calorie intake is necessary to maintain good health. At the point when your Body Mass Index is somewhere in between from 25 to 29. It implies that you are conveying overabundance weight. Assuming your BMI is more than 30, it implies you have obesity. To get in shape or keep up the solid weight individuals needs to monitor the calorie they take. The existing system calorie estimation is to be happened manually. The proposed model is to provide unique solution for measuring calorie by using deep learning algorithm. The food calorie calculation is very important in medical field. Because this food calorie is provide good health condition. This measurement is taken from food image in different objects that is fruits and vegetables. This measurement is taken with the help of neural network. The tensor flow is one of the best methods to classify the machine learning method. This method is implementing to calculate the food calorie with the help of Convolutional Neural Network. The input of this calculated model is taken an image of food. The food calorie value is calculated the proposed CNN model with the help of food object detection. The primary parameter of the result is taken by volume error estimation and secondary parameter is calorie error estimation. The volume error estimation is gradually reduced by 20%. That indicates the proposed CNN model is providing higher accuracy level compare to existing model. 2021 IEEE. -
Food and communities in post-COVID-19 cities: Case of India
While Covid-19 pandemic has affected countries across the world, the burden has been shared disproportionately by urban poor from the cities in Global South. In much of Global South, while cities have emerged as growth centers, they are mostly driven by informalities, belying the image of cities, visualized in the mainstream development economics literature as a place of secured formal jobs that free one from the drudgery of rural life. Covid-19 pandemic has exposed these fault-lines in the cities. India serves as a typical case of such urban-centric growth, with informal workers, predominated by disadvantaged social and religious categories, accounting for 81% of workers in urban space. In cities, migrant in general and seasonal migrants increasingly account for bulk of informal workforce. The lockdown imposed in the wake of Covid-19 pandemic left the community of households reliant on informal works for livelihoods, without any rights and entitlements, which affect their access to food. The review of evidence collected in both primary surveys and macro level data points towards sluggishness in recovery of jobs, which coupled with high food inflation, suggests that access to food continues to be an issue in urban governance. The paper calls for a roadmap entailing both short-term and long-term measures to build sustainable urban livelihoods for ensuring food secure urban space in India. 2023 The Author(s) -
Food Additives and Evolved Methods of Detection: A Review
Food additives are essential constituents of food products in the modern world. The necessity of food processing went up rapidly as to meet requirements including, imparting desirable properties like preservation, enhancement and regulation of color and taste. The methods of identification and analysis of such substances are crucial. With the advancement of technology, a variety of techniques are emerging for this purpose which have many advantages over the existing conventional ways. This review is on different kinds of additives used in the food industry and few prominent methods for their determination ranging from conventional chromatographic techniques to the recently evolved nano-sensor techniques. 2024 Taylor & Francis Group, LLC. -
Food additives and contaminants in infant foods: a critical review of their health risk, trends and recent developments
The infant food market has expanded rapidly over the past two decades. However, the industry faces significant challenges, including concerns over the health effects of infant food additives and issues with food safety. However, new evidences suggest that certain food additives, such as those used to preserve and transport infant formula to keep it fresh for longer, should be avoided. Science into the effects of additives on human behavior makes up a sizable sector of the additives market. Problems such as hypernatremic dehydration, malnutrition, and obesity in infants are directly linked to faulty formula production. The Food and Drug Administration (FDA) has established the toxicity types and chemical tests necessary for evaluating the safety of food additives and GRAS (Generally Recognized as Safe) compounds. These tests are crucial in understanding the food safety aspects of food additives. The health effects of different types of food additives on infants are discussed in this context. The article gives an outline of various national and global agencies that provides recommendations and standards to gauge the quality of baby food. The immunological responses, allergic reaction pathways and other related health hazards among the infants and young children caused by the food additive are discussed in this article. Graphical Abstract: (Figure presented.) The Author(s) 2024. -
Folksonomy-based fuzzy user profiling for improved recommendations
Genre is a major factor influencing user decisions to peruse an item in domains such as movies, books etc. Recommender systems, generally have, at their disposal, information regarding genres/categories that a movie/book belongs to. However, the degree of membership of the objects in these categories is typically unavailable. Such information, if available, would provide a better description of items and consequently lead to quality recommendations. In this paper, we propose an approach to infer the degree of genre presence in a movie by examining the various tags conferred on them by various users. Tags are user-defined metadata for items and embed abundant information about various facets of user likes, their opinion on the quality and the type of object tagged. Leveraging on tags to guide the genre degree determination exploits crowd sourcing to enrich item content description. Fuzzy logic naturally models human logic allowing for the nuanced representation of features of objects and thus is utilized to derive such gradual representation as well as for modeling user profiles. To the best of our knowledge ours is one of the first approaches to utilize such folksonomy information to infer genre degrees subsequently used for recommendations. The proposed method has the twin advantages of utilizing enriched content information for recommendation as well as squeezing the information from the user-item-tag and user-item ratings spaces and condensing them into fuzzy user profiles. The fuzzy user and object representations are leveraged both for the design of content-based as well as collaborative recommender systems. Experimental evaluations establish the effectiveness of the proposed approaches as compared to other baselines. 2013 Elsevier Ltd. All rights reserved. -
Folic Acid-Modified B-Type Y2O3:Eu3+ Quantum Dots: A Bright Approach to Fluorescence Imaging of Cancer Cells
Clinical applications of nanophosphors have gained extensive interest in research areas such as bioimaging and targeted drug delivery. The development of nontoxic semiconductor quantum dots (QDs), which can replace the conventional fluorescent probes, can bring significant developments in the bioimaging industry. This work reports the synthesis of monoclinic Y2O3:Eu QDs, without and with surface functionalization using PEG/folic acid at low temperature and its application in live cancer cell imaging. The synthesized quantum dots show sharp absorption in the short UV region and an intense red emission at 614 nm. Concentration-dependent optical properties are studied in detail, and color purity is measured. Transmission electron microscopy substantiates the monoclinic structure, crystalline nature, and the lower particle dimensions essential for the biological applications. The surface-modified sample is characterized for its structural and luminescence properties. Biocompatibility was ensured by performing MTT Assay on L6 skeletal muscle cell lines (normal) and MCF 7 cell lines (cancer) for the samples without and with surface modification, respectively. Fluorescence detection experiments on SKMEL cells using an uncapped sample prove the suitability of the material as a fluorescent probe. The effect of surface functionalization on imaging results was established by carrying out fluorescence detection experiments on MCF 7 cells using PEG-folic acid-functionalized sample, which resulted in enhanced cell uptake, specific binding, and bright fluorescence emission. Thus, this work authenticates the suitability of the material to be used as a reliable nanophosphor and an efficient fluorescent probe for imaging cancer cells. 2024 American Chemical Society. -
Foetal brain extraction using mathematically modelled local foetal minima
This paper proposes segmentation techniques to separate brain parcel from the MRI of the human embryo and also determines the abnormality of the foetal brain at various gestational weeks. These strategies mean to characterise areas of the premium of various granularities: brain, tissue types, or constructions that are more limited. Various philosophies have been applied for this division task and can be grouped into the solo, parametric, characterisation, atlas combination, and deformable models. Brain atlases are usually used as preparing information in the division interaction. Difficulties identifying using pictures secured, the quick mental health, and the restricted accessibility of imaging information thwart this division task. This paper discusses foetal brain segmentation using mathematically modelled foetal brain minima by using a curve fitting segmentation technique. Broad tests show that the proposed approach beats the ebb and flow of various segmentation techniques and the results gained are significant. Copyright 2023 Inderscience Enterprises Ltd. -
FO-DPSO Algorithm for Segmentation and Detection of Diabetic Mellitus for Ulcers
In recent days, the major concern for diabetic patients is foot ulcers. According to the survey, among 15 people among 100 are suffering from this foot ulcer. The wound or ulcer found which is found in diabetic patients consumes more time to heal, also required more conscious treatment. Foot ulcers may lead to deleterious danger condition and also may be the cause for loss of limb. By understanding this grim condition, this paper proposes Fractional-Order Darwinian Particle Swarm Optimization (FO-DPSO) technique for analyzing foot ulcer 2D color images. This paper deals with standard image processing, i.e. efficient segmentation using FO-DPSO algorithm and extracting textural features using Gray Level Co-occurrence Matrix (GLCM) technique. The whole effort projected results as accuracy of 91.2%, sensitivity of 100% and specificity as 96.7% for Nae Bayes classifier and accuracy of 91.2%, sensitivity of 100% and sensitivity of 79.6% for Hoeffding tree classifier. 2023 World Scientific Publishing Company. -
Fluorescent PVDF dots: from synthesis to biocidal activity
Infection by microorganisms is a serious concern in food storage, water purification, drugs, and particularly in biomedical devices. Long-term use of permanent implants often leads to its contamination due to pathogens. Timely tracking of bacterial activity and its interaction with antibodies are crucial for overcoming these infections. In this work, fluorescent polymeric biocides are obtained from a non-conjugated polymer polyvinylidene fluoride (PVDF), which is neither emissive nor known for its antibacterial activity. PVDF dot was synthesized via hydrothermal treatment eliminating the need for complicated and toxic preparation strategies. PVDF-based dot exhibits high fluorescence aroused from the carbogenic core due to the carbonization of the hydrocarbon chain. It is found that the dots were semiconducting contrary to the bulk form of PVDF. The photoluminescent polymer dots also exhibited an excellent antibacterial activity toward Escherichia coli (E.coli) and Streptococcus bacteria. This luminescence and biocidal activity of PVDF-derived dots have attractive applications in the field of fluorescent diagnostics and therapeutics. Graphical abstract: [Figure not available: see fulltext.] 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. -
Fluorescent Photosensitizers: A Promising Tool for Biomedicine
The growing demand for the detection for biomedical imaging has taken the interest of researchers as there is a significant increase in cancer and malignant diseases across the globe. Photosensitizers assisted with fluorescent properties can be a pioneer in this field. Photosensitizers generally damage the living cell, however, selected fluorescent photosensitizers can offer a minimal threat to the living cells. Medically relevant processes such as live cell imaging and photodynamic therapy can be monitored using this technique. Some of the commonly used fluorescent photosensitizers include porphyrins, chlorins, and bacteriochlorins. This chapter addresses the significance, limitations, and future perspectives of fluorescent photosensitizers in biological applications. Scientists can develop efficient fluorescent photosensitizers for easy detection and cure of different infectious diseases. The chapter also puts forward a deeper understanding of the principle underlying tunable fluorescent properties, and the recent efforts for developing efficient fluorescent photosensitizers. 2022 Nova Science Publishers, Inc. -
Fluorescent Mechanism in Zero-Dimensional Carbon Nanomaterials: A Review
Fluorescent carbon dots (CDs) have acquired growing interest from different areas over decades. Their fascinating property of tunable fluorescence by changing the excitation wavelength has attracted researchers worldwide. Understanding the mechanisms behind fluorescence is of great importance, as they help with the synthesis and applications, significantly when narrowed down to applications with color-tunable mechanisms. But, due to a lack of practical and theoretical information, the fluorescence mechanisms of CDs remain unknown, preventing the production of CDs with desired optical qualities. This review focuses on the PL mechanisms of carbon dots. The quantum confinement effect determined the carbon core, the surface and edge states determined by various surface defects and the connected functional/chemical groups on the surface/edges, the molecular state solely determined the fluorophores in the interior or surface of the CDs, and the Crosslink Enhanced Emission Effect are the currently confirmed PL mechanisms. Graphic Abstract: [Figure not available: see fulltext.]. 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Fluorescent imidazole derived sensor for selective in vitro and in vivo Fe2+ detection and bioimaging in zebrafish with DFT studies
Herein, we have developed imidazole derivatized fluorescent probes IM-1 and IM-2 for extremely selective detection of Fe2+ with rapid response (LOD: 3.245 ?M for IM-1 and 0.297 ?M for IM-2) and excellent binding constants (0.214 105 M?1 and 1.004 105 M?1). Aqueous ethanol system was employed to assess the sensing potency of the probes both in vitro and in vivo in zebrafish is the main highlight of this work. The synthesized fluorophores possess admirable quantum yields of 0.61 and 0.78. The 1:1 binding mechanism of ligands with Fe2+ ions is supported by Job's plot and ESI-Mass spectrum. The synthesized probes demonstrated limited cytotoxicity both in vitro (MDA-MB-231 cells) and in vivo (zebrafish, Danio Rerio) studies. These results prompted us to employ the probes IM-1 and IM-2 to trace out intra cellular Fe2+ ions in zebrafish embryos. 2024 Elsevier B.V. -
Fluorescent enhancement of polymer nanoparticle by composite preparation with ruta graveolens nano-carbon and its application in fluorescence sensing /
Patent Number: 202241039689, Applicant: Neethu Joseph.
The current invention provides an environmentally friendly, green synthesis of a cost- effective and scalable nanocarbon-polymer composite with possible fluorescence features that may be used in fluorescence sensing. The fluorescence of the produced nanostructure is high, indicating that this could be employed in fluorescence-based sensing applications. Fluorescence spectroscopy experiments show that the produced nano-carbon has remarkable heavy metal ion sensing potential.