利用计算机视觉进行水果检测，快速可靠地测定橄榄油质量。

Fast and Reliable Determination of Virgin Olive Oil Quality by Fruit Inspection Using Computer Vision.

机构信息

Robotics, Automation and Computer Vision Group, Electronic and Automation Engineering Department, University of Jaen, ES-23071 Jaen, Spain.

出版信息

Sensors (Basel). 2018 Nov 8;18(11):3826. doi: 10.3390/s18113826.

DOI:10.3390/s18113826

PMID:30413055

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6263641/

Abstract

The presence of minor compounds in virgin olive oils has been proven to play multiple positive roles in health protection, encouraging its production. The key factors that influence the oil quality are ripening stages and the state of health of the fruit. For this reason, at the oil mill's reception yard, fruits are visually inspected and separated according to their external appearance. In this way, the process parameters can be better adjusted to improve the quantity and/or quality of olive oil. This paper presents a proposal to automatically determine the oil quality before being produced from a previous inspection of the incoming fruits. Expert assessment of the fruit conditions guided the image processing. The proposal has been validated through the analysis of 74 batches of olives coming from an oil mill. Best correlation results between the image processing and the analytical data were found in the acidity index, peroxide values, ethyl ester, polyphenols, chlorophylls, and carotenoids.

摘要

初榨橄榄油中微量化合物的存在已被证明在健康保护方面发挥了多种积极作用，这鼓励了其生产。影响油质的关键因素是成熟阶段和果实的健康状况。因此，在油厂的接收场地上，根据果实的外观对果实进行目视检查和分类。通过这种方式，可以更好地调整工艺参数，以提高橄榄油的数量和/或质量。本文提出了一种在生产前自动确定油质的建议，该建议是基于对即将进入生产阶段的果实的前期检查。果实状况的专家评估指导了图像处理。该建议已通过对来自一家油厂的 74 批橄榄的分析进行了验证。在酸度指数、过氧化物值、乙酯、多酚、叶绿素和类胡萝卜素方面，图像处理和分析数据之间的相关性最佳。