41 resultados para Sustainable Food Systems


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This paper provides an overview of concepts of sustainable agriculture and possible methods of attaining sustainability of agricultural yields and production. Reasons are given as to why modern industrialised agriculture might be less sustainable in terms of yields than traditional agriculture. The question of whether organic agriculture is likely to be more sustainable than non-organic agriculture is considered as well as organic agriculture’s likely impact on wild biodiversity. The impact of the development of agriculture on wild biodiversity is assessed because some environmentalists see the conservation of wild biodiversity as an important ingredient of sustainable development. However, there is a policy conflict between conservationist groups. Some see intensive agriculture (including silviculture) as favourable to the conservation of wild biodiversity whereas others oppose such production methods as being unfavourable to wild biodiversity conservation. Reasons why modern industrialised agricultural systems are so widely adopted (and continue to be adopted) despite their apparent lack of sustainability are suggested. Market systems may tend to lock producers into unsustainable production methods.

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The purpose of this study was threefold: first, the study was designed to illustrate the use of data and information collected in food safety surveys in a quantitative risk assessment. In this case, the focus was on the food service industry; however, similar data from other parts of the food chain could be similarly incorporated. The second objective was to quantitatively describe and better understand the role that the food service industry plays in the safety of food. The third objective was to illustrate the additional decision-making information that is available when uncertainty and variability are incorporated into the modelling of systems. (C) 2002 Elsevier Science B.V. All rights reserved.

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Dynamic rheological behaviour of starch-honey systems was studied using a strain-controlled rheometer. A dynamic temperature (30-130 degreesC) ramp test was used at 10 rad s(-1) frequency, 1% strain, 2 degreesC min(-1) ramp rate, 25 mm parallel plate, and 1.5 min gap, using Wheaten cornflour(TM) and five honeys to generate 25 formulations (0.34-0.80 g water/g dry starch). G', G, and eta* increased upon gelatinisation, and they reduced as the honey content was increased. For all the formulations, G' was higher than G, and tan 6 was generally less than 1.0. Key gelatinisation characterising temperatures (onset, peak and end) ranged from 96.0 to 122.3 degreesC, but did not vary much (CV < 5%) for each honey irrespective of the concentration. The influence of water, fructose and glucose, singly and in combination, on gelatinisation indices (temperature and rheological parameters) was investigated. An exponential equation was employed to describe the relationship, and relevant parameters were obtained. The consequences of the observations in the study are discussed particularly as they relate to extrusion of such systems, and possible interactions between fructose and glucose in the starch-honey systems. (C) 2003 Elsevier Ltd. All rights reserved.

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Increasing interests in the use of starch as biodegradable plastic materials demand, amongst others, accurate information on thermal properties of starch systems particularly in the processing of thermoplastic starch (TPS), where plasticisers (water and glycerol) are added. The specific heat capacity of starch-water-glycerol mixtures was determined within a temperature range of 40-120degreesC. A modulated temperature differential scanning calorimeter (MTDSC) was employed and regression equations were obtained to predict the specific heat capacity as a function of temperature, water and glycerol content for four maize starches of differing amylose content (0 - 85%). Generally, temperature and water content are directly proportional to the specific heat capacity of the systems, but the influence of glycerol content on the thermal property varied according to the starch type.

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Smallholder farming systems in Papua New Guinea are characterised by an integrated set of cash cropping and subsistence food cropping activities. In the Highlands provinces, the subsistence food crop sub-system is dominated by sweet potato production. Coffee dominates the cash cropping sub-system, but a limited number of food crops are also grown for cash sale. The dynamics between sub-systems can influence the scope for complementarity between, and technical efficiency of, their operations, especially in light of the seasonality of demand for household labour and management inputs within the farming system. A crucial element of these dynamic processes is diversification into commercial agricultural production, which can influence factor productivity and the efficiency of crop production where smallholders maintain a strong production base in subsistence foods. In this study we use survey data from households engaged in coffee and food crop production in the Benabena district of Eastern Highlands Province to derive technical efficiency indices for each household over two years. A stochastic input distance function approach is used to establish whether diversification economies exist and whether specialisation in coffee, subsistence food or cash food production significantly influences technical efficiency on the sampled smallholdings. Diversification economics are weakly evident between subsistence food production and both coffee and cash food production, but diseconomies of diversification are discerned between coffee and cash food production. A number of factors are tested for their effects on technical efficiency. Significant technical efficiency gains are made from diversification among broad cropping enterprises.

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Aims: To determine the prevalence and concentration of Escherichia coli O157 shed in faeces at slaughter, by beef cattle from different production systems. Methods and Results: Faecal samples were collected from grass-fed (pasture) and lot-fed (feedlot) cattle at slaughter and tested for the presence of E. coli O157 using automated immunomagnetic separation (AIMS). Escherichia coli O157 was enumerated in positive samples using the most probable number (MPN) technique and AIMS and total E. coli were enumerated using Petrifilm. A total of 310 faecal samples were tested (155 from each group). The geometric mean count of total E. coli was 5 x 10(5) and 2.5 x 10(5) CFU g(-1) for lot- and grass-fed cattle, respectively. Escherichia coli O157 was isolated from 13% of faeces with no significant difference between grass-fed (10%) and lot-fed cattle (15%). The numbers of E. coli O157 in cattle faeces varied from undetectable (

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The recent summary report of a Department of Energy Workshop on Plant Systems Biology (P.V. Minorsky [2003] Plant Physiol 132: 404-409) offered a welcomed advocacy for systems analysis as essential in understanding plant development, growth, and production. The goal of the Workshop was to consider methods for relating the results of molecular research to real-world challenges in plant production for increased food supplies, alternative energy sources, and environmental improvement. The rather surprising feature of this report, however, was that the Workshop largely overlooked the rich history of plant systems analysis extending over nearly 40 years (Sinclair and Seligman, 1996) that has considered exactly those challenges targeted by the Workshop. Past systems research has explored and incorporated biochemical and physiological knowledge into plant simulation models from a number of perspectives. The research has resulted in considerable understanding and insight about how to simulate plant systems and the relative contribution of various factors in influencing plant production. These past activities have contributed directly to research focused on solving the problems of increasing biomass production and crop yields. These modeling approaches are also now providing an avenue to enhance integration of molecular genetic technologies in plant improvement (Hammer et al., 2002).

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Sugars affect the gelatinization of starch, with the effect varying significantly between sugars. Since many food products contain a mixture of sugar sources, it is important to understand how their mixtures affect starch gelatinization. In a Rapid Visco Analyser study of maize starch gelatinization, changing proportions in binary mixtures of refined sugars saw a largely proportionate change in starch gelatinization properties. However, binary mixture of pure sugars and honey, or a model honey system (the main sugars in honey) and honey responded differently. Generally, replacing 25% or 50% of the refined sugar or model honey system with honey gave a large change in starch gelatinization properties, while further increases in honey level had little further effect. Differences between honey and buffered model honey system (either gluconic acid, or a mixture of citric acid and di-sodium phosphate) showed the sensitivity of starch gelatinization to the composition of the nonsaccharide component. (c) 2004 Swiss Society of Food Science and Technology. Published by Elsevier Ltd. All rights reserved.

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Cereal-legume intercropping plays an important role in subsistence food production in developing countries, especially in situations of limited water resources. Crop simulation can be used to assess risk for intercrop productivity over time and space. In this study, a simple model for intercropping was developed for cereal and legume growth and yield, under semi-arid conditions. The model is based on radiation interception and use, and incorporates a water stress factor. Total dry matter and yield are functions of photosynthetically active radiation (PAR), the fraction of radiation intercepted and radiation use efficiency (RUE). One of two PAR sub-models was used to estimate PAR from solar radiation; either PAR is 50% of solar radiation or the ratio of PAR to solar radiation (PAR/SR) is a function of the clearness index (K-T). The fraction of radiation intercepted was calculated either based on Beer's Law with crop extinction coefficients (K) from field experiments or from previous reports. RUE was calculated as a function of available soil water to a depth of 900 mm (ASW). Either the soil water balance method or the decay curve approach was used to determine ASW. Thus, two alternatives for each of three factors, i.e., PAR/SR, K and ASW, were considered, giving eight possible models (2 methods x 3 factors). The model calibration and validation were carried out with maize-bean intercropping systems using data collected in a semi-arid region (Bloemfontein, Free State, South Africa) during seven growing seasons (1996/1997-2002/2003). The combination of PAR estimated from the clearness index, a crop extinction coefficient from the field experiment and the decay curve model gave the most reasonable and acceptable result. The intercrop model developed in this study is simple, so this modelling approach can be employed to develop other cereal-legume intercrop models for semi-arid regions. (c) 2004 Elsevier B.V. All rights reserved.

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The principles of sustainable development (or ecologically sustainable development as it is known in Australia) are now accepted as the foundation for natural resource management worldwide and there are increasing community expectations that they will be implemented explicitly. Previous attempts to assess sustainable development for fisheries have mostly failed because the methods have been too restrictive, often attempting to develop a single set of indicators. In 2000, all the fishery agencies and major stakeholder groups in Australia supported the development of a National ESD Framework. This initiative resulted in a practical system being generated through the results of a series of case studies and stakeholder workshops. The Australian National ESD Framework divides ESD into eight major components within the three main categories of ecological well-being, human well-being and ability to contribute: Four main steps are used to complete an ESD report for a fishery: (1) identify relevant issues, (2) prioritise these using risk assessment, (3) complete appropriately detailed reports on each issue and (4) compile the material into a report. The tools to assist this process are now available and have been used to generate reports for many Australian fisheries. (C) 2004 Elsevier B.V. All rights reserved.