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Prediction of the antioxidant capacity of maize (Zea mays) hybrids using mass fingerprinting and data mining
Food Bioscience ( IF 4.8 ) Pub Date : 2020-07-03 , DOI: 10.1016/j.fbio.2020.100647
Josaphat Miguel Montero-Vargas , Sofia Ortíz-Islas , Obed Ramírez-Sánchez , Silverio García-Lara , Robert Winkler

Hybrid maize (Zea mays L.) is one of the major grains used as food for humans and animals. Besides carbohydrates and amino acids, maize contains micronutrients such as vitamins and phytochemicals with health-promoting effects. In a current maize breeding program, the phytochemical profiles of 35 maize hybrids grown in three significant agroecologies of Mexico - highlands, subtropics and tropics - were evaluated. For the different locations, phytochemical traits, which are relevant for nutraceutical effects, and the antioxidative capacity, were determined. Statistical analyses indicate the importance of the pedigree/agroecology on the phytochemical profiles. Mass fingerprinting in combination with the Random Forest Tree algorithm allowed the building of models that predicted the antioxidative capacity of the maize hybrids. The methods are, therefore, suitable for the efficient selection of maize hybrids with improved nutraceutical value.



中文翻译:

利用大量指纹图谱和数据挖掘预测玉米(Zea mays)杂种的抗氧化能力。

杂交玉米(Zea mays)L.)是用作人类和动物食物的主要谷物之一。玉米除了碳水化合物和氨基酸外,还含有微量营养素,例如维生素和植物化学物质,具有促进健康的作用。在当前的玉米育种计划中,评估了在墨西哥的三种重要农业生态系统(高地,亚热带和热带)中生长的35种玉米杂交种的植物化学特征。对于不同的位置,确定了与营养保健作用和抗氧化能力相关的植物化学特性。统计分析表明,谱系/农业生态学对植物化学特征的重要性。大量指纹分析与随机森林树算法相结合,可以建立预测玉米杂交种抗氧化能力的模型。因此,这些方法是

更新日期:2020-07-03
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