24 resultados para FOOD TECHNOLOGY


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The agronomic and economic performance of genetically modified (GM) crops relative to their conventional counterparts has been largely investigated worldwide. As a result there is considerable information to conduct a meta-analysis to evaluate the agronomic and economic relative performance of GM crops vs. non GM crops by crop, GM trait, and country’s level of development. Such meta-analysis has been recently conducted showing that overall GM crops outperform non GM crops in both agronomic and economic terms (1). This paper focuses on the agronomic and economic performance of GM crops in developing and developed countries as well as the potential implications for global food security of adoption of GM crops by developing countries. The presumption that technology only benefits the developed world is not supported by the meta-analysis conducted. No evidence that GM technology benefits moredeveloped than developing countries was found. Indeed, the agronomic and economic performance of GM crops vs. conventional crops tends to be better for developing than for developed countries. Although it is manifested that the conventional agronomic practices in developing countries are different to those in developed countries, it is also apparent that GM crop adoption in developing countries may help to tackle the growing concerns over the scarcity of food globally.

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In the ten years since the first edition of this book appeared there have been significant developments in food process engineering, notably in biotechnology and membrane application. Advances have been made in the use of sensors for process control, and the growth of information technology and on-line computer applications continues apace. In addition, plant investment decisions are increasingly determined by quality assurance considerations and have to incorporate a greater emphasis on health and safety issues. The content of this edition has been rearranged to include descriptions of recent developments and to reflect the influence of new technology on the control and operations of automated plant. Original examples have been retained where relevant and these, together with many new illustrations, provide a comprehensive guide to good practice.

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Agriculture and food security are key sectors for intervention under climate change. Agricultural production is highly vulnerable even to 2C (low-end) predictions for global mean temperatures in 2100, with major implications for rural poverty and for both rural and urban food security. Agriculture also presents untapped opportunities for mitigation, given the large land area under crops and rangeland, and the additional mitigation potential of aquaculture. This paper presents a summary of current knowledge on options to support farmers, particularly smallholder farmers, in achieving food security through agriculture under climate change. Actions towards adaptation fall into two broad overlapping areas: (1) accelerated adaptation to progressive climate change over decadal time scales, for example integrated packages of technology, agronomy and policy options for farmers and food systems, and (2) better management of agricultural risks associated with increasing climate variability and extreme events, for example improved climate information services and safety nets. Maximization of agriculture’s mitigation potential will require investments in technological innovation and agricultural intensification linked to increased efficiency of inputs, and creation of incentives and monitoring systems that are inclusive of smallholder farmers. Food systems faced with climate change need urgent, broad-based action in spite of uncertainties.

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Tremendous progress in plant proteomics driven by mass spectrometry (MS) techniques has been made since 2000 when few proteomics reports were published and plant proteomics was in its infancy. These achievements include the refinement of existing techniques and the search for new techniques to address food security, safety, and health issues. It is projected that in 2050, the world’s population will reach 9–12 billion people demanding a food production increase of 34–70% (FAO, 2009) from today’s food production. Provision of food in a sustainable and environmentally committed manner for such a demand without threatening natural resources, requires that agricultural production increases significantly and that postharvest handling and food manufacturing systems become more efficient requiring lower energy expenditure, a decrease in postharvest losses, less waste generation and food with longer shelf life. There is also a need to look for alternative protein sources to animal based (i.e., plant based) to be able to fulfill the increase in protein demands by 2050. Thus, plant biology has a critical role to play as a science capable of addressing such challenges. In this review, we discuss proteomics especially MS, as a platform, being utilized in plant biology research for the past 10 years having the potential to expedite the process of understanding plant biology for human benefits. The increasing application of proteomics technologies in food security, analysis, and safety is emphasized in this review. But, we are aware that no unique approach/technology is capable to address the global food issues. Proteomics-generated information/resources must be integrated and correlated with other omics-based approaches, information, and conventional programs to ensure sufficient food and resources for human development now and in the future.

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There are well-known difficulties in making measurements of the moisture content of baked goods (such as bread, buns, biscuits, crackers and cake) during baking or at the oven exit; in this paper several sensing methods are discussed, but none of them are able to provide direct measurement with sufficient precision. An alternative is to use indirect inferential methods. Some of these methods involve dynamic modelling, with incorporation of thermal properties and using techniques familiar in computational fluid dynamics (CFD); a method of this class that has been used for the modelling of heat and mass transfer in one direction during baking is summarized, which may be extended to model transport of moisture within the product and also within the surrounding atmosphere. The concept of injecting heat during the baking process proportional to the calculated heat load on the oven has been implemented in a control scheme based on heat balance zone by zone through a continuous baking oven, taking advantage of the high latent heat of evaporation of water. Tests on biscuit production ovens are reported, with results that support a claim that the scheme gives more reproducible water distribution in the final product than conventional closed loop control of zone ambient temperatures, thus enabling water content to be held more closely within tolerance.

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Background: Advances in nutritional assessment are continuing to embrace developments in computer technology. The online Food4Me food frequency questionnaire (FFQ) was created as an electronic system for the collection of nutrient intake data. To ensure its accuracy in assessing both nutrient and food group intake, further validation against data obtained using a reliable, but independent, instrument and assessment of its reproducibility are required. Objective: The aim was to assess the reproducibility and validity of the Food4Me FFQ against a 4-day weighed food record (WFR). Methods: Reproducibility of the Food4Me FFQ was assessed using test-retest methodology by asking participants to complete the FFQ on 2 occasions 4 weeks apart. To assess the validity of the Food4Me FFQ against the 4-day WFR, half the participants were also asked to complete a 4-day WFR 1 week after the first administration of the Food4Me FFQ. Level of agreement between nutrient and food group intakes estimated by the repeated Food4Me FFQ and the Food4Me FFQ and 4-day WFR were evaluated using Bland-Altman methodology and classification into quartiles of daily intake. Crude unadjusted correlation coefficients were also calculated for nutrient and food group intakes. Results: In total, 100 people participated in the assessment of reproducibility (mean age 32, SD 12 years), and 49 of these (mean age 27, SD 8 years) also took part in the assessment of validity. Crude unadjusted correlations for repeated Food4Me FFQ ranged from .65 (vitamin D) to .90 (alcohol). The mean cross-classification into “exact agreement plus adjacent” was 92% for both nutrient and food group intakes, and Bland-Altman plots showed good agreement for energy-adjusted macronutrient intakes. Agreement between the Food4Me FFQ and 4-day WFR varied, with crude unadjusted correlations ranging from .23 (vitamin D) to .65 (protein, % total energy) for nutrient intakes and .11 (soups, sauces and miscellaneous foods) to .73 (yogurts) for food group intake. The mean cross-classification into “exact agreement plus adjacent” was 80% and 78% for nutrient and food group intake, respectively. There were no significant differences between energy intakes estimated using the Food4Me FFQ and 4-day WFR, and Bland-Altman plots showed good agreement for both energy and energy-controlled nutrient intakes. Conclusions: The results demonstrate that the online Food4Me FFQ is reproducible for assessing nutrient and food group intake and has moderate agreement with the 4-day WFR for assessing energy and energy-adjusted nutrient intakes. The Food4Me FFQ is a suitable online tool for assessing dietary intake in healthy adults.

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In this paper we employ a hypothetical discrete choice experiment (DCE) to examine how much consumers are willing to pay to use technology to customize their food shopping. We conjecture that customized information provision can aid in the composition of a healthier shop. Our results reveal that consumers are prepared to pay relatively more for individual specic information as opposed to generic nutritional information that is typically provided on food labels. In arriving at these results we have examined various model specications including those that make use of ex-post de-brieng questions on attribute nonattendance and attribute ranking information and those that consider the time taken to complete the survey. Our main results are robust to the various model specications we examine