相关实验视频

Updated: Jun 22, 2025

Simultaneous Long-term Recordings at Two Neuronal Processing Stages in Behaving Honeybees

Simultaneous Long-term Recordings at Two Neuronal Processing Stages in Behaving Honeybees

Published on: July 21, 2014

基于同位素和元素含量与ANNs的关联,开发具有广泛适用的蜂蜜识别模型

Ariana Raluca Hategan¹, Adriana Dehelean², Romulus Puscas²

¹National Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donat Street, 400293 Cluj-Napoca, Romania; Faculty of Physics, Babeș-Bolyai University, Kogălniceanu 1, 400084 Cluj-Napoca, Romania.

|June 29, 2024

概括

人工神经网络 (ANN) 可以使用同位素和元素数据来验证蜂蜜的来源和收获年份. 这种方法达到超过86%的准确性,为蜂蜜改提供了可扩展的解决方案.

科学领域:

食品科学食品科学食品科学
分析化学分析化学
数据科学数据科学数据科学

背景情况:

蜂蜜改,特别是植物来源和收获年份的错误声明,在全球范围内构成了重大经济挑战.
现有的认证方法可能不够精确,无法处理复杂的伪造技术.

研究的目的:

评估人工神经网络 (ANN) 在预测蜂蜜的植物起源和收获年份方面的有效性.
开发可靠的预测模型,使用同位素和元素指纹进行蜂蜜认证.

主要方法:

人工神经网络 (ANN) 在分类任务中的应用.
使用同位素和元素组成作为模型的输入特征.
严格的数据预处理以优化模型性能.

主要成果:

在测试阶段,ANN模型实现了超过86%的分类准确性,无论是植物来源还是收获年.
这些模型在鉴定蜂蜜的真实性方面表现出有效性,尽管植物来源,地理位置和收获期的差异不同.

结论:

蜂蜜认证网络提供了一种有效和准确的蜂蜜认证方法,特别是用于确定植物来源和收获年份.
开发的模型显示了在打击蜂蜜欺诈方面大规模应用的高可行性.

关键词:

人工智能的人工智能是人工智能.人工神经网络的人工神经网络一个基本的元素概况.蜂蜜验证蜂蜜验证蜂蜜验证稳定的同位素比率是稳定的.

更多相关视频

Deep Neural Networks for Image-Based Dietary Assessment

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

Tactile Conditioning And Movement Analysis Of Antennal Sampling Strategies In Honey Bees Apis mellifera L.

Tactile Conditioning And Movement Analysis Of Antennal Sampling Strategies In Honey Bees Apis mellifera L.

Published on: December 12, 2012

相关概念视频

Mass Spectrometry: Isotope Effect

Mass Spectrometry: Isotope Effect

Most elements exist in nature as a mixture of isotopes. The isotopes differ in weight due to their respective number of neutrons. The molecular weight of a molecule is different depending on the specific isotope of its elements involved. As a result, the mass spectrum of the molecule exhibits peaks from the same fragment at multiple positions. The positions of these mass signals depend on the difference between the molecular mass. Furthermore, the intensity of these signals is dependent on the...

¹³C NMR: ¹H–¹³C Decoupling

¹³C NMR: ¹H–¹³C Decoupling

The probability of having two carbon-13 atoms next to each other is negligible because of the low natural abundance of carbon-13. Consequently, peak splitting due to carbon-carbon spin-spin coupling is not observed in spectra. However, protons up to three sigma bonds away split the carbon signal according to the n+1 rule, resulting in complicated spectra.
A broadband decoupling technique is used to simplify these complex, sometimes overlapping, signals. Broadband decoupling relies on a...