894 resultados para food supply chains
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2016
Resumo:
Smart Farming Technologies (SFT) is a term used to define the set of digital technologies able not only to control and manage the farm system, but also to connect it to the many disruptive digital applications posed at multiple links along the value chain. The adoption of SFT has been so far limited, with significant differences at country-levels and among different types of farms and farmers. The objective of this thesis is to analyze what factors contributes to shape the agricultural digital transition and to assess its potential impacts in the Italian agri-food system. Specifically, this overall research objective is approached under three different perspectives. Firstly, we carry out a review of the literature that focuses on the determinants of adoption of farm-level Management Information Systems (MIS), namely the most adopted smart farming solutions in Italy. Secondly, we run an empirical analysis on what factors are currently shaping the adoption of SFT in Italy. In doing so, we focus on the multi-process and multi-faceted aspects of the adoption, by overcoming the one-off binary approach often used to study adoption decisions. Finally, we adopt a forward-looking perspective to investigate what the socio-ethical implications of a diffused use of SFT might be. On the one hand, our results indicate that bigger, more structured farms with higher levels of commercial integration along the agri-food supply chain are those more likely to be early adopters. On the other hand, they highlight the need for the institutional and organizational environment around farms to more effectively support farmers in the digital transition. Moreover, the role of several other actors and actions are discussed and analyzed, by highlighting the key role of specific agri-food stakeholders and ad-hoc policies, with the aim to propose a clearer path towards an efficient, fair and inclusive digitalization of the agrifood sector.
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Industria 4.0 ha coinvolto il settore agroalimentare introducendo nuove strategie di tracciabilità, a favore della sostenibilità e della sicurezza alimentare. L’Organizzazione Internazionale della Vigna e del Vino pone tra gli obiettivi per il 2024 la transizione digitale della filiera, così da avere una tracciabilità trasparente e affidabile. Questo fornisce un vantaggio ai produttori e ai consumatori che dispongono di maggiori informazioni quantitative e qualitative del prodotto. I sistemi di tracciabilità sono integrati nella supply chain aumentandone la resilienza; tuttavia, la maggior parte degli ERP in commercio ricostruiscono la tracciabilità a posteriori: dal codice lotto finale si ricompone tutto il processo. Per monitorare costantemente la filiera ed incrementarne la trasparenza si stanno integrando nuove tecnologie alla tracciabilità, come l’intelligenza artificiale e la blockchain. Obiettivo di questa tesi è la progettazione di un sistema di tracciabilità blockchain. Pertanto, si introduce alla tracciabilità e alla blockchain descrivendo i principali contributi in letteratura che propongono approcci e strategie, evidenziando vantaggi e sfide future. Poi, si presenta il caso Moncaro, cooperativa agricola che ha cantine e vigneti nel territorio marchigiano, analizzando il processo di vinificazione in bianco dal punto di vista del flusso fisico e informativo, rispettivamente tramite BPMN e Relationship chart. Ai fini della modellazione e della scelta dei dati da inserire in tracciabilità, si analizzano le informazioni registrate negli ERP sviluppati da Apra s.p.a., software house, di cui Moncaro fruisce. Quindi, si propone la formulazione di un algoritmo in pseudocodice che permette di collegare sequenzialmente le attività, così, da ottenere la tracciabilità real time e un’architettura che può gestire tutte le informazioni della supply chain. Infine, si è implementato uno scenario produttivo reale, mediante l’architettura di database a grafo di Neo4j AuraDB
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The purpose of this paper is to provide a comparative analysis of pork value chains in Catalonia, Spain and Manitoba, Canada. Intensive hog production models were implemented in Catalonia in the 1960s as a result of agriculture crises and fostered by feedstuffs factories. The expansion of the hog sector in Manitoba is more recent (in the 1990s) and brought about in large part by the opening of the Maple Leaf Meats processing plant in Brandon, Manitoba. This plant is capable of processing 90,000 hogs per week. Both hog production models ‐ the ‘older’ one in Catalonia (Spain) and the ‘newer’ in Manitoba‐ have been, until recently, examples of success. Inventories and production have been increasing substantially and both regions have proven to have great export potential. Recently, however, tensions have been developing with the hog production models of both regions, particularly as they relate to environmental concerns. The purpose of the paper is to compare the value chains with respect to their origins (e.g. supply a growing demand for pork, ensure farm profitability) and present states (e.g. environmental concerns, profitability). Keywords: pork value chain, hog farms, agri‐food studies. JEL: Q10, Q13, O57
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Agricultural policy liberalisation, concern about unhealthy diets and growing recognition of the importance of sustainable land use have fostered interest in the development of competitive food chains based around products that are beneficial to the rural environment. We review the potential for foods with enhanced health attributes based on alternative varieties/breeds and production systems to traditional agriculture which has been predominantly motivated by yields. We concentrate on soft fruit, which is an important source of polyphenols, and grazing livestock systems that have the potential for improving fatty acid profiles in meat products and find there to be clear scientific potential, but limited research to date. Consumer research suggests considerable acceptance of such products and willingness to pay sufficient to cover additional production costs. Purchase of such foods could have major implications for agricultural land use and the rural environment. There is little research to date on specific healthier food products, but spatially explicit models are being developed to assess land use and environmental implications of changing demand and husbandry methods.
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The purpose of the paper is to identify and describe differences in cognitive structures between consumer segments with differing levels of acceptance of genetically modified (GM) food. Among a sample of 60 mothers three segments are distinguished with respect to purchase intentions for GM yogurt: non-buyers, maybe-buyers and likely-buyers. A homogeneity test for the elicited laddering data suggests merging maybe- and likely-buyers, yielding two segments termed accepters and rejecters. Still, overlap between the segments’ cognitive structures is considerable, in particular with respect to a health focus in the evaluation of perceived consequences and ambivalence in technology assessment. Distinct differences are found in the assessment of benefits offered by GM food and the importance of values driving product evaluation and thus purchase decisions.
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In the UK there is widespread support from Government, media and consumers for local food networks. These have the potential to provide a more sustainable supply chain and are well suited to the unique production and consumption characteristics of horticultural products. In terms of food marketing, local food is in its relative infancy and is still without any formal definition. This lack of clarity hampers research activities. Although the profile of local food buyers and their expectations has been explored, our knowledge of its social, economic and environmental aspects is minimal. This research contributes by exploring the structure and scope of local food activities in the UK in terms of profiling those specialised retail outlets who provide consumers with the opportunity to purchase locally grown horticultural products.
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New models for estimating bioaccumulation of persistent organic pollutants in the agricultural food chain were developed using recent improvements to plant uptake and cattle transfer models. One model named AgriSim was based on K OW regressions of bioaccumulation in plants and cattle, while the other was a steady-state mechanistic model, AgriCom. The two developed models and European Union System for the Evaluation of Substances (EUSES), as a benchmark, were applied to four reported food chain (soil/air-grass-cow-milk) scenarios to evaluate the performance of each model simulation against the observed data. The four scenarios considered were as follows: (1) polluted soil and air, (2) polluted soil, (3) highly polluted soil surface and polluted subsurface and (4) polluted soil and air at different mountain elevations. AgriCom reproduced observed milk bioaccumulation well for all four scenarios, as did AgriSim for scenarios 1 and 2, but EUSES only did this for scenario 1. The main causes of the deviation for EUSES and AgriSim were the lack of the soil-air-plant pathway and the ambient air-plant pathway, respectively. Based on the results, it is recommended that soil-air-plant and ambient air-plant pathway should be calculated separately and the K OW regression of transfer factor to milk used in EUSES be avoided. AgriCom satisfied the recommendations that led to the low residual errors between the simulated and the observed bioaccumulation in agricultural food chain for the four scenarios considered. It is therefore recommended that this model should be incorporated into regulatory exposure assessment tools. The model uncertainty of the three models should be noted since the simulated concentration in milk from 5th to 95th percentile of the uncertainty analysis often varied over two orders of magnitude. Using a measured value of soil organic carbon content was effective to reduce this uncertainty by one order of magnitude.
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Modern food systems are characterized by a high energy intensity as well as by the production of large amounts of waste, residuals and food losses. This inefficiency presents major consequences, in terms of GHG emissions, waste disposal, and natural resource depletion. The research hypothesis is that residual biomass material could contribute to the energetic needs of food systems, if recovered as an integrated renewable energy source (RES), leading to a sensitive reduction of the impacts of food systems, primarily in terms of fossil fuel consumption and GHG emissions. In order to assess these effects, a comparative life cycle assessment (LCA) has been conducted to compare two different food systems: a fossil fuel-based system and an integrated system with the use of residual as RES for self-consumption. The food product under analysis has been the peach nectar, from cultivation to end-of-life. The aim of this LCA is twofold. On one hand, it allows an evaluation of the energy inefficiencies related to agro-food waste. On the other hand, it illustrates how the integration of bioenergy into food systems could effectively contribute to reduce this inefficiency. Data about inputs and waste generated has been collected mainly through literature review and databases. Energy balance, GHG emissions (Global Warming Potential) and waste generation have been analyzed in order to identify the relative requirements and contribution of the different segments. An evaluation of the energy “loss” through the different categories of waste allowed to provide details about the consequences associated with its management and/or disposal. Results should provide an insight of the impacts associated with inefficiencies within food systems. The comparison provides a measure of the potential reuse of wasted biomass and the amount of energy recoverable, that could represent a first step for the formulation of specific policies on the integration of bioenergies for self-consumption.