A new ecological diversity approach for evaluation of black tea samples: α-indices

Sebahattin Serhat TURGUT, Ebru DOĞAN, Volkan ÖĞÜZ, Sibel ŞAHİN, Zuhal AKKAŞOĞLU, Erkan KARACABEY, Erdoğan KÜÇÜKÖNER

Department of Food Engineering, Faculty of Engineering, Suleyman Demirel University, Isparta, Turkeye-mail: serhatturgut@sdu.edu.tr

INTRODUCTIONIn order to conduct an idea about the quality of tea samples, a number of different analytical and sensorial test are performed inthe industry. In the present study, a new and simple alternative to these analysis are presented to assess different tea samplesusing responses of their water extracts against visible spectrum. For that purpose ecology based α-indices were employed. Inecology, briefly, alpha diversity (α-diversity) means species diversity in sites or habitats at a local scale. Here, it was used to evaluatethe variation in the spectrum data of tea extracts.

AIM Chemometric techniques are widely

used in classification studies due toits ease of apply, comparably lesstime and economic requirementscompared to other analyticalmethods.

Thus, in the present study, it wasaimed to investigate the possibility ofclassify different black tea samplesproduced using 21 different tealeaves harvested from varyingaltitudes employing α-indicesaccording to their responces againstvisible spectrum.

METHOD Twenty one different tea samples ensured from a national tea producer in Turkey. The samples were delivered to laboratory in pre-encoded form with random three digit

numbers. Thus, the possible similarities/dissimilarities between samples were notknown by the researchers before study.

2 g of tea samples were extracted in boiling water for 10 min then filtered through afilter paper. After the extracts were let for 10 min to cool down to room temperature, 1ml was taken and diluted in 30 ml of distilled water before readings.

Absorbance spectrums of the tea samples were determined between 190-1000 nmusing a UV-VIS spectrophotometer however the absorbance data against visiblespectrum at 354-406 nm were used as characteristic region.

The most common α-divesity indices, namely Simpson (S), Shannon-Wiener (SW),Evenness (E), Brillouin (B) and Menhinick (M) indices, were calculated directly fromabsorbance data using PAST3 statistical analysis software.

*For more detail please check Özkan, K. 2016. Biyolojik çeşitlilik bileşenleri (α, β ve γ) nasıl ölçülür?, Süleyman Demirel Üniversitesi Yayınevi, Isparta.

Moreover a cluster analysis were made in order to group samples according to theirdiversity scores.

RESULTS

CONCLUSIONThese results indicated that the chemometricapproach with α-diversity indices is an easy andsuccessful option for classification of teasamples. According the promising results, thesetechniques have a great potential to be furtherused in food industry.

In the results above, according to the clustering (classical euclidean) study, two main groups may beconsidered among the 21 tea samples with respect to alfa diversity indices and these random codedsamples can be classified under 5-7 differet sub-groups depending on sensitivity of the analysis.

AcknowledgementThe statistical calculations in the present study were perfomed with the help of precious education named TÜBİTAK 2229-BİDEP ‘’Biyolojik Çeşitlilik Ölçüm Süreçleri: Envanter, Veri Transferi ve Hesaplama Teknikleri’’ (Project No: 1129B371800485). Thus, wewould like to thank to project executives.

RandomSampleCodes

Simpson Std. Dev.Shannon-Wiener

Std. Dev. Evenness Std. Dev. Brillouin Std. Dev. Menhinick Std. Dev.

823 0.0306 0.0002 3.5693 0.0040 0.9097 0.0037 0.3630 0.0353 12.5333 1.2355

819 0.0309 0.0003 3.5607 0.0055 0.9024 0.0049 0.4144 0.0032 14.5867 0.2237

268 0.0310 0.0004 3.5617 0.0075 0.9033 0.0070 0.3977 0.0154 13.8467 0.7580

928 0.0311 0.0002 3.5613 0.0006 0.9028 0.0005 0.4175 0.0266 14.8967 1.5184

527 0.0314 0.0003 3.5527 0.0047 0.8948 0.0041 0.4171 0.0174 14.8833 0.9411

618 0.0322 0.0010 3.5413 0.0168 0.8851 0.0145 0.4089 0.0271 14.7067 1.6358

975 0.0324 0.0008 3.5370 0.0122 0.8812 0.0111 0.4381 0.0106 16.2867 0.8416

263 0.0324 0.0011 3.5353 0.0197 0.8796 0.0174 0.3835 0.0300 13.6333 1.5007

854 0.0326 0.0012 3.5317 0.0231 0.8765 0.0202 0.3900 0.0239 13.8967 1.2352

365 0.0326 0.0006 3.5310 0.0087 0.8759 0.0078 0.4063 0.0068 14.5667 0.3287

461 0.0326 0.0016 3.5363 0.0248 0.8806 0.0224 0.4441 0.0137 16.7667 1.2702

184 0.0330 0.0016 3.5237 0.0318 0.8697 0.0278 0.4251 0.0098 15.6333 0.2540

724 0.0332 0.0013 3.5220 0.0208 0.8678 0.0181 0.4300 0.0134 15.9967 1.0598

733 0.0332 0.0006 3.5227 0.0119 0.8687 0.0101 0.4669 0.0040 18.6667 0.3963

762 0.0336 0.0006 3.5130 0.0096 0.8601 0.0082 0.4073 0.0165 14.8500 0.7673

156 0.0337 0.0013 3.5107 0.0231 0.8586 0.0200 0.4198 0.0214 15.5633 1.4049

752 0.0337 0.0007 3.5120 0.0095 0.8594 0.0084 0.4299 0.0071 16.0667 0.5762

857 0.0346 0.0008 3.5000 0.0142 0.8494 0.0121 0.4474 0.0024 17.4267 0.3661

629 0.0358 0.0003 3.4793 0.0061 0.8318 0.0053 0.4673 0.0123 19.4500 1.2668

437 0.0366 0.0011 3.4633 0.0188 0.8186 0.0154 0.4545 0.0106 18.5033 0.6842

568 0.0397 0.0044 3.4220 0.0742 0.7869 0.0572 0.4789 0.0082 21.6567 1.7992

CO

NTA

CT

PO

STER