Characterization and Discrimination of Apples by Flash GC E-Nose: Geographical Regions and Botanical Origins Studies in China

Abstract

Forty-one apple samples from 7 geographical regions and 3 botanical origins in China were investigated. A total of 29 volatile compounds have been identified by flash GC E-nose. They are 17 esters, 5 alcohols, 3 aldehydes, 1 ketone, and 3 others. A principal component analysis was employed to study the relationship between varieties and volatiles. A partial least squares discriminant analysis (PLS-DA), stepwise linear discriminant analysis (SLDA), and decision tree (DT) are used to discriminate apples from 4 geographical regions (34 apple samples) and 3 botanical origins (36 apple samples). The most influential markers identified by PLS-DA are 2-hexadecanone, methyl decanoate, tetradecanal, 1,8-cineole, hexyl 2-butenoate, (Z)-2-octenal, methyl 2-methylbutanoate, ethyl butyrate, dimethyl trisulfide, methyl formate, ethanol, S(-)2-methyl-1-butanol, ethyl acetate, pentyl acetate, butyl butanoate, butyl acetate, and ethyl octanoate. From the present work, SLDA reveals the best discrimination results in geographical regions and botanical origins, which are 88.2% and 88.9%, respectively. Although machine learning DT is attempted to classify apple samples, the results are not satisfactory.

Unmasking the ‘Asymptomatic’ COVID-19: A Nose Question

“…Specifically, the stimuli used in identification tests are qualitative and identification suffers from cultural biases, cognitive ability, and olfactory ‘alphabetization’; for instance, a common stimulus of this tests whether the natural peppermint is a mixture of at least 20 pure odorants [ 36 ] and whether apple is a mixture of at least 37 odorants, which include n-butanol [ 37 ]. To explain the complexity of the qualitative tests, carvone, which is one of the odorants in peppermint, has two stereoisomers: one smells of caraway (the S-(+)) and the other of mint (the R-(−)).…”

“…To explain the complexity of the qualitative tests, carvone, which is one of the odorants in peppermint, has two stereoisomers: one smells of caraway (the S-(+)) and the other of mint (the R-(−)). Again, isoamylacetate at varying concentrations gives a different perception that can vary from banana to pear, but is also contained in the smell of apple [ 37 ]. To try to overcome these obstacles, the rapid identification test was shaped by removing the odorants apple, turpentine, and garlic from the original test because they were identified by less than 55% of the normosmic validation cohort.…”

Analyzing the Quality Parameters of Apples by Spectroscopy from Vis/NIR to NIR Region: A Comprehensive Review

“…However, spectroscopic methods may see competition from the GC in head-space mode (i.e., Flash GC) in this area of applications. The technique also offers a non-destructive and non-contaminating manner of analysis, while delivering a molecular fingerprint of volatiles by applying chemometrics to process the chromatograms; it has been successfully applied in the analysis of agri-food items including apples [100,101]. On the other hand, Zhu et al [102] explored the use of hyperspectral imaging in a 400-1000 nm wavelength window (i.e., in Vis and Vis/NIR regions) for evaluating the aroma components of hybrid apple offspring.…”

Rapid analysis technologies with chemometrics for food authenticity field: A review

“… Authenticity problem Technology Product category Food product Adulterants/classified product Instrument configuration Chemometrics method Discriminant rate References Breeds/Species identification E-nose Animal Meat Minced meat, 2 Species: mutton and pork a PEN2 E-nose (portable electronic nose II, Airsense Corpora-tion, Germany) SLDA – Tian et al (2013) Plant Baijiu 6 Breeds: Strong aroma, Soy sauce aroma, Light aroma, Jian aroma, Feng aroma and Herbal aroma the fast GC- based electronic nose analysis, Heracles II (Alpha MOS, Toulouse, France) PLS-DA 93.94% He et al (2021) Fruit Apple, 3 Breeds: Golden Delicious, Fuji and Ralls an FGC E-nose (Heracles II, Alpha M.O.S., Toulouse, France) SLDA 87.5% Wu et al (2022) Red wine, 3 Breeds: Cabernet Sauvignon, Snake Dragon Ball and Merlot colorimetric sensors in the E-nose system a E-tongue (Isenso, Shanghai Ruifen International Trading Co., Ltd.) ELM 100% Han et al (2020) E-tongue Animal Meat Cattle, 5 Breeds: Angus, domestic buffalo, Hungarian Grey, Hungarian Spotted cattle and Holstein a potentiometric electronic tongue (e-tongue) with food grade sensors LDA 100% Suranyi et al (2021) Minced meat, 3 Species: mutton, pork and chicken the taste system of a-Astree (Alpha M.O.S, Toulouse, France) BDA, CDA 90%–100% …”

“…The results showed a total classification accuracy of 91.53% and 93.94% for aroma and region, respectively. Wu et al (2022) analyzed 41 apple samples from seven regions and three plant sources in China using an E-nose, identifying 29 volatile compounds. The algorithm identification rates were 88.2% and 88.9% for the geographical regions and plant sources, respectively.…”