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Abstract：
A large section of the human population relies on legumes as a staple food. Legumes are a rich source of nutrients and possess several health-related beneficial properties. However, the nutritional quality of legumes is challenged by the presence of a considerable amount of antinutrients. Consumption of inadequately processed legumes might affect normal metabolism and cause adverse human health-related effects. Effective processing becomes necessary to reduce these antinutritional factors before consumption. Optimizing the processing variables during preparation of legume-based traditional foods by using response surface methodology could be a valuable option to reduce antinutrients. The present review focuses on the efficacy of traditional household-scale processing unit operations vis-à-vis the reduction of antinutrients. Optimally prepared products should ensure meeting the consumer demand of improved, healthy, and more nutritious and safe foods. Modeling-based optimization approach will be helpful to define best practices at the small-, medium-, and large scale production alike. It should contribute towards effective utilization of legume resources, and to alleviate malnutrition and associated diseases world-wide.
摘要：
很大一部分人口依赖豆类作为主食。豆类是丰富的营养来源，具有几种与健康相关的有益特性。然而,豆类的营养质量受到大量抗营养素存在的挑战。食用加工不当的豆类可能会影响正常的新陈代谢并引起与人类健康相关的不利影响。有效的处理对于在消费之前减少这些抗营养因素是必要的。通过使用响应面法优化豆类传统食品制备过程中的加工变量可能是减少抗营养素的有价值的选择。本审查的重点是传统的家庭规模的处理单元操作相对于减少抗营养素的功效。优化制备的产品应确保满足消费者的改进需求，健康,和更有营养和安全的食物。基于建模的优化方法将有助于在小规模、medium-,和大规模生产一样。它应该有助于有效利用豆类资源，并减轻全世界的营养不良和相关疾病。
