Intelligence detection of oil absorption in French fries by surface profiles.
Intelligence detection of oil absorption in French fries by surface profiles.
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DOI：
10.1016/j.foodres.2023.113906
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发表时间：
2024-02
影响因子：
8.1
通讯作者：
Simeng Wang;Shuli Zhao;Nan Wang;Qianru Lu;Haile Zhao;Ying Liu;Jinwei Li;Liuping Fan
中科院分区：
文献类型：
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作者：
Simeng Wang;Shuli Zhao;Nan Wang;Qianru Lu;Haile Zhao;Ying Liu;Jinwei Li;Liuping Fan
表面形貌是评价油炸食品吸油性能的重要指标。基于炸薯条表面特征，建立了偏最小二乘回归（PLSR）和BP神经网络（BP-ANN）两种智能模型，用于炸薯条吸油行为的监测。研究了菜籽油（RO）和高油酸花生油（HOPO）在不同温度下对炸薯条表面形貌和质构的影响。结果表明，随着油炸温度的升高，样品的含油量增加，分别占RO和HOPO油炸样品的37.7%和41.4%。随着油炸温度的升高，脆皮率、粗糙度和质构参数（Fm、Nwr、fwr、Wc）增加，均匀度降低。PLSR和BP-ANN模型预测集的相关系数均大于0.93，表明表面特征结合化学计量学是快速、准确测定薯条含油量的方法。
Surface profiles are important evaluation indices for oil absorption behavior of fried foods. This research established two intelligent models of partial least-squares regression (PLSR) and back propagation artificial neural network (BP-ANN) for monitoring the oil absorption behavior of French fries based on the surface characteristics. Surface morphology and texture of French fries by rapeseed oil (RO) and high-oleic peanut oil (HOPO) at different temperatures were investigated. Results showed that oil content of samples increased with frying temperature, accounting for 37.7% and 41.4% of samples fried by RO and HOPO respectively. The increase of crust ratio, roughness and texture parameters (Fm, Nwr, fwr, Wc) and the decrease of uniformity were observed with the frying temperature. Coefficients of prediction set of PLSR and BP-ANN models were more than 0.93, which indicated that surface features combined with chemometrics were rapid and precise methods for determining the oil content of French fries.