Leiqing Pan

TL;DR: E-nose was able to realise the early diagnosis of fungal disease, in addition to an accurate classification of the pathogenic fungal type in the fruits during post-harvest storage, by identifying several key characteristic volatile compounds for each infection treatment.

TL;DR: Feelability of hyperspectral reflectance imaging technique for detecting cold injury is demonstrated and the overall classification accuracy of chill damage was 95.8% for all cold-stored samples.

TL;DR: Wang et al. as mentioned in this paper applied a portable electronic nose to objectively assess twenty most favorable and commercially available Chinese spirits, and the responsive value obtained from electronic nose measurement provided strong evidence that sensor S1 (aromatic compounds, toluene), S3 (aromorphic compounds, ammonia), S5 (alkenes, aromatic compounds), S6 (broad-methane), S7 (sulphur-organic) and S9 (aromatics compounds, sulphur- organic) could be applied to assess spirits.

TL;DR: The results showed that changes in volatile compounds in fungi-inoculated peaches were correlated with total amounts and species of fungi, and Partial Least Squares Regression (PLSR) could effectively be used to predict fungal colony counts in peach samples.

TL;DR: In this paper, the authors used visible and near-infrared spectroscopy coupled with partial least squares regression to predict the moisture, soluble solids and sucrose content and mechanical properties of sugar beet.