scholarly journals Additivity between Key Odorants in Pig House Air

Atmosphere ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1008
Author(s):  
Michael Jørgen Hansen ◽  
Anders Peter S. Adamsen ◽  
Chuandong Wu ◽  
Anders Feilberg

The verification of odor abatement technologies for livestock production based on chemical odorants requires a method for conversion into an odor value that reflects the significance of the individual odorants. The aim of the present study was to compare the SOAV method (Sum of Odor Activity Values) with the odor detection threshold measured by olfactometry and to investigate the assumption of additivity. Synthetic pig house air with odorants at realistic concentration levels was used in the study (hydrogen sulfide, methanethiol, trimethylamine, butanoic acid, and 4-methylphenol). An olfactometer with only PTFE in contact with sample air was used to estimate odor threshold values (OTVs) and the odor detection threshold for samples with two to five odorants. The results show a good correlation (R2 = 0.88) between SOAV estimated based on the OTVs for panelists in the present study and values found in the literature. For the majority of the samples, the ratio between the odor detection threshold and SOAV was not significantly different from one, which indicates that the OAV for individual odorants in a mixture can be considered additive. In conclusion, the assumption of additivity between odorants measured in pig house air seems reasonable, but the strength of the method is determined by the OTV data used.

2013 ◽  
Vol 807-809 ◽  
pp. 451-455 ◽  
Author(s):  
Di Fang ◽  
Jie Min Liu ◽  
Qin Yi

The amount of sample can enter the nasal cavity depends on the physiochemical characteristics such as distribution, volatility and solubility. It can be suspected that the difference of odor detection threshold (ODT) measured by different methods is related to the physicochemical properties of compounds. To investigate the relationship between ODT differences and the physicochemical properties of compounds, ODT values of four series of organic compounds were measured by triangle odor bag method and gas chromatography and olfactometry method; the results were compared and the absolute differences were calculated. Relationship between ODT differences and the type of functional group and some of the physicochemical properties of compounds was analyzed. The results showed the type of functional group had significant effect on the differences. Certain linear relationships between the logarithmic value of differences and the logarithmic values of saturated vapor pressure and molecular weight were observed.


Foods ◽  
2018 ◽  
Vol 7 (11) ◽  
pp. 176 ◽  
Author(s):  
Marianne McKay ◽  
Florian Bauer ◽  
Valeria Panzeri ◽  
Astrid Buica

The odor detection threshold (ODT) of a compound is the lowest concentration at which individuals can reliably perceive a difference between a sample and its corresponding control, with 50% performance above chance. Wine is a complex matrix, and ODTs used in studies on wine can be based on inappropriate matrices and informal sensory methodologies. Formal studies confirming ODTs in wine are relatively scarce in the literature, and are complex and expensive to carry out. In this study, the sensitivity of panelists to previously published ODTs for five compounds: Guaiacol, o-cresol and 4-ethyl phenol, 3-isobutyl-2-methoxypyrazine (IBMP), and 2,4,6-trichloroanisole (TCA) associated with off-flavor/taint issues in wine, was investigated. The study was carried out in partially de-aromatized young Shiraz wine (unwooded) using a simplified version of the formal sensory approach. A triangle test in triplicate was carried out with 34 panelists, at the ODT for each compound, in one day. The study explored whether previous training affected panelists’ sensitivity for threshold differences. Results showed that samples spiked with volatile phenols were significantly different (p = 0.01) to controls. The spiked TCA and IBMP samples were not significantly different from the control in either case. Judges were better able to detect compounds if they had prior experience or training in wine evaluation. Despite some limitations, this pragmatic approach may be useful when carrying out sensory studies with fairly limited resources and within tight timelines, as it provides helpful information on panel members and detection thresholds for a specific matrix.


2011 ◽  
Vol 20 (7) ◽  
pp. 333-340 ◽  
Author(s):  
Iva Dudova ◽  
Jan Vodicka ◽  
Marketa Havlovicova ◽  
Zdenek Sedlacek ◽  
Tomas Urbanek ◽  
...  

2020 ◽  
Vol 17 (10) ◽  
pp. 1021-1030 ◽  
Author(s):  
Hye Ri Kim ◽  
Sun Mi Kim ◽  
Wonshik Seong ◽  
Hyun Jin Min ◽  
Kyung Soo Kim ◽  
...  

Objective We aimed to find the optimal cut-off scores for screening of odor detection threshold, odor discrimination, and odor identification tests for detection of mild cognitive impairment (MCI) and dementia in Korean elderly.Methods A total of 195 elderly people were divided into three groups: the normal cognition (NC), MCI, and dementia groups. All participants underwent neurocognitive and olfactory function tests. We used k-means cluster analysis and receiver operating characteristic (ROC) analysis to identify the most appropriate cut-off value.Results To distinguish the MCI from NC groups, odor identification [area under the curve (AUC)=0.670, p<0.007] with a cut-off point of 7 showed greater validity for screening (sensitivity/specificity=0.462/0.837) than did other olfactory function tests. To distinguish the MCI and dementia from NC as well, odor identification (AUC=0.817, p=0.002) with a cut-off point of 7 showed the highest validity for screening (0.785/0.654). To distinguish MCI from AD, an odor detection threshold (AUC=0.722, p=0.001) with a cut-off point of 2 showed the highest validity for screening (0.785/0.654).Conclusion Olfactory function tests may be a useful screening tool for cognitive decline before clinical symptoms of dementia have completely developed. This tool can be used as a supplementary tool to enhance the sensitivity of traditional cognitive tests to screen for dementia.


2010 ◽  
Vol 35 (8) ◽  
pp. 727-734 ◽  
Author(s):  
L. V. Sondergaard ◽  
I. E. Holm ◽  
M. S. Herskin ◽  
F. Dagnaes-Hansen ◽  
M. G. Johansen ◽  
...  

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