首页> 外文期刊>Journal of Food Security >Neglected and Underutilized Legumes (NULs): Exposure Assessment, Habitual Cooking and Eating Habits and Consumers’ Characteristics
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Neglected and Underutilized Legumes (NULs): Exposure Assessment, Habitual Cooking and Eating Habits and Consumers’ Characteristics

机译:被忽视和利用不足的豆类(NUL):暴露评估,惯常的烹饪和饮食习惯以及消费者的特征

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Many people usually consume neglected and underutilized legumes (NULs) as stop gap diets, making the legumes a critical food security resource. In order to ensure their sustainability, a survey was designed to study the characteristics of 534 respondents towards NULs processing and consumption. The survey questions covered habitual thermal processing times of NULs seeds, the quantities of NULs dishes consumed and the number of times they were consumed per week. Other questions covered consumer characteristics such as age, body weight, educational background, occupation, marital status and household numbers. The statistical analysis used Palisade @Risk software to fit each study item to the most adequate probabilistic distribution, based on their Akaike information criterion. Subsequently, the central tendency characteristics of the studied items together with their variations and uncertainties were recorded. The results showed quantified exposure assessment of each NUL, obtained as an integration of the product of the amount of NULs dishes consumed and the exposure frequency of each NULs dishes consumed per body weights of consumers. Similarly, the output of consumer characteristics were recorded along the statistical distributions of each specific NUL’s consumption. These were linked to the ages of individuals consuming it, the household numbers of consumers, the educational levels, marital status and the occupation of the respondents.
机译:许多人通常食用被忽略和未充分利用的豆类作为间隙饮食,使豆类成为重要的粮食安全资源。为了确保其可持续性,设计了一项调查,以研究534名被调查者对NUL加工和消费的特征。调查问题涵盖了NULs种子的惯常热处理时间,食用的NULs菜的数量以及每周食用它们的次数。其他问题涉及消费者特征,例如年龄,体重,教育背景,职业,婚姻状况和家庭人数。统计分析基于Akaike信息标准,使用Palisade @Risk软件将每个研究项目拟合到最适当的概率分布。随后,记录了研究项目的集中趋势特征及其变化​​和不确定性。结果显示了每个NUL的量化暴露评估,该评估是消耗的NUL菜量与每单位消费者体重消耗的每个NUL菜的暴露频率乘积的积分。同样,消费者特征的输出沿每个NUL特定消费的统计分布进行记录。这些因素与个人消费年龄,消费者家庭人数,受教育程度,婚姻状况和受访者的职业有关。

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