950 resultados para Cooking (Vegetables)--Recipes
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2 of 2
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Includes index.
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Mode of access: Internet.
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Mode of access: Internet.
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Includes index.
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Mode of access: Internet.
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"Zoology": p. 361-407.
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"Additions" and "Corrections": [4] p. at end.
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Mode of access: Internet.
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The thermal properties of soft and hard wheat grains, cooked in a steam pressure cooker, as a function of cooking temperature and time were investigated by modulated temperature differential scanning calorimetry (MTDSC). Four cooking temperatures (110, 120, 130 and 140 degrees C) and six cooking times (20, 40, 60, 80, 100 and 120 min) for each temperature were studied. It was found that typical non-reversible heat flow thermograms of cooked and uncooked wheat grains consisted of two endothermic baseline shifts localised around 40-50 degrees C and then 60-70 degrees C. The second peaks of non-reversible heat flow thermograms (60-70 degrees C) were associated with starch gelatinisation. The degree of gelatinisation was quantified based on these peaks. In this study, starch was completely gelatinised within 60-80 min for cooking temperatures at 110-120 degrees C and within 20 min for cooking temperatures at 130-140 degrees C. MTDSC detected reversible endothermic baseline shifts in most samples, localised broadly around 48-67 degrees C with changes in heat capacity ranging from 0.02 to 0.06 J/g per degrees C. These reversible endothermic baseline shifts are related to the glass transition, which occurs during starch gelatinisation. Data on the specific heat capacity of the cooked wheat samples are provided. (C) 2005 Elsevier Ltd. All rights reserved.
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Understanding the particularly low intake of fruits and vegetables among socioeconomically disadvantaged groups is an important issue for public health. This study investigated whether access to retail outlets is similar across areas of varying socioeconomic disadvantage in an Australian urban setting, in terms of distance, the numbers of local shops, and their opening hours. This ecological cross-sectional study used 50 randomly sampled census collection districts and their nearby shopping environment (i.e. within 2.5 km), and generally found minimal or no socioeconomic differences in shopping infrastructure. Important methodological and social/economic issues may explain this contrast with overseas findings.