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在塞维利亚式绿橄榄碱液处理过程中使用人工视觉确定终止烹饪过程的最佳时间。

Use of Artificial Vision during the Lye Treatment of Sevillian-Style Green Olives to Determine the Optimal Time for Terminating the Cooking Process.

作者信息

Gordillo Miguel Calixto López, Madueño-Luna Antonio, Luna José Miguel Madueño, Ramírez-Juidías Emilio

机构信息

Graphics Engineering Department, University of Seville, 41013 Seville, Spain.

Aeroespace Engineering and Fluid Mechanical Department, University of Seville, 41013 Seville, Spain.

出版信息

Foods. 2023 Jul 24;12(14):2815. doi: 10.3390/foods12142815.

DOI:10.3390/foods12142815
PMID:37509907
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10379037/
Abstract

This study focuses on characterizing the temporal evolution of the surface affected by industrial treatment with NaOH within the processing tanks during the lye treatment stage of Manzanilla table olives. The lye treatment process is affected by multiple variables, such as ambient temperature, the initial temperature of the olives before lye treatment, the temperature of the NaOH solution, the concentration of the solution, the variety of olives, and their size, which are determinants of the speed of the lye treatment process. Traditionally, an expert, relaying on their subjective judgement, manages the cooking process empirically, leading to variability in the termination timing of the cook. In this study, we introduce a system that, by using an artificial vision system, allows us to know in a deterministic way the percentage of lye treatment achieved at each moment along the cooking process; furthermore, with an interpolator that accumulates values during the lye treatment, it is possible to anticipate the completion of the cooking by indicating the moment when two-thirds, three-fourths, or some other value of the interior surface will be reached with an error of less than 10% relative to the optimal moment. Knowing this moment is crucial for proper processing, as it will affect subsequent stages of the manufacturing process and the quality of the final product.

摘要

本研究着重于表征在曼萨尼拉餐用橄榄的碱液处理阶段,加工槽内经过氢氧化钠工业处理的表面随时间的演变情况。碱液处理过程受多种变量影响,如环境温度、碱液处理前橄榄的初始温度、氢氧化钠溶液的温度、溶液浓度、橄榄品种及其大小,这些都是碱液处理过程速度的决定因素。传统上,由专家凭借主观判断对烹饪过程进行经验管理,这导致烹饪终止时间存在差异。在本研究中,我们引入了一个系统,该系统通过使用人工视觉系统,使我们能够以确定性的方式了解在整个烹饪过程中每个时刻碱液处理所达到的百分比;此外,借助一个在碱液处理过程中累积数值的内插器,能够通过指出内表面达到三分之二、四分之三或其他某个值的时刻,以相对于最佳时刻小于10%的误差来预测烹饪的完成情况。知道这个时刻对于正确加工至关重要,因为它会影响制造过程的后续阶段以及最终产品的质量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/74ce/10379037/c250023fda77/foods-12-02815-g012.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/74ce/10379037/c250023fda77/foods-12-02815-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/74ce/10379037/701ab55d4ea0/foods-12-02815-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/74ce/10379037/5fabd8a1deae/foods-12-02815-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/74ce/10379037/b7fddf79b57d/foods-12-02815-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/74ce/10379037/594c243de3ba/foods-12-02815-g004.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/74ce/10379037/dc06abfff55a/foods-12-02815-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/74ce/10379037/7fd18b04d7b1/foods-12-02815-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/74ce/10379037/9953e56901b9/foods-12-02815-g009.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/74ce/10379037/c250023fda77/foods-12-02815-g012.jpg

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A Machine Vision Rapid Method to Determine the Ripeness Degree of Olive Lots.机器视觉快速测定法在橄榄批量成熟度检测中的应用。
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Table Olives: An Overview on Effects of Processing on Nutritional and Sensory Quality.油橄榄:加工对营养和感官品质影响的综述
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