Determination of Classification Model and Total Phenolic Content of Local Variety Soursop (Annona muricata L.) Leaf Powder in Different Altitudes Using NIR and FTIR Spectroscopy with Chemometrics

Abstract

Soursop (Annona muricata L.) leaves have been widely used traditionally to overcome health problems, this is related to its total phenolic content. This study was aimed to determine the classification model and total phenolic content of soursop leaf powder of local varieties, in different altitudes using Near Infrared (NIR) and Fourier-transform Infrared(FTIR) spectroscopy with chemometrics. Local variety soursop leaf samples that have been collected from low land (0-200 meter above sea level (masl)), medium land (201-700 masl) and high land (>700 masl) were prepared and then scanned using NIR and FTIR spectroscophotometers. Furthermore, the NIR spectra data from the samples were used as predictors on the LDA classification model of local and queen varieties soursop leaves to identify the sample varieties. Samples identified as local varieties, whose total phenolic content was determined using a comparative method (UV-Vis spectrophotometry). The highest mean of total phenolic content was observed in samples from medium land (Jember) of 5.72% w/w Gallic Acid Equivalent (GAE), followed by low land (Bangkalan) 2.95% w/w GAE and high land (Batu) 1.78% w/w GAE. NIR and FTIR spectra data belonging to the samples were analyzed by chemometrics qualitatively using LDA, SVM and SIMCA, and quantitatively using PLS, PCR and SVR. The best classification and calibration model are formed from the NIR spectra data, that are the LDA model with an accuracy of 100% and the PLS model with an R-square calibration value of 0.998071 and RMSEC of 1.2735631. The LDA and PLS models are applied to the real samples. The results of the sample's total phenolic content determination obtained from the NIR spectroscopy method and UV-Vis spectrophotometry method were then tested with Paired-Samples T Test and it can be concluded that the content obtained from the two methods did not have a significant different.

Determination of Total Phenolic Content and NIR-Chemometrics Classification Model of Queen and Local Varieties of Soursop (<i>Annonamuricata</i> L.) Leaf Powder

“…After 100% accuracy of prediction was obtained, LDA and SVM models were then validated by cross validation. In this study, the validations were Leave-One-Out-Cross Validation and 2-Fold-Cross-Validation, because it has been proven effective for validating the classification chemometric model in previous studies [15,22]. The results of Leave-One-Out-Cross Validation obtained in this study were 100% accurate.…”

“…Determination of total phenolic content was carried out by pipetting 100 µL of each standard solution and the sample solution then added with 500 µL of Folin-Ciocalteu (1:10 v/v water). Then the mixture was incubated for 6 min, and then added with 400 µL Na2CO3 (7.5 % w/v water) [15][16]. The mixture was then allowed to stand at room temperature during the incubation time, and later the absorbance was measured at the optimum wavelength.…”

Determination of Total Phenolic Content and Total Flavonoid Content of Nutmeg Flesh (Myristica Fragrans Houtt) Ethanol Extract from South Aceh Province

“…al. [19] method. Extract of nutmeg flesh weighed 20 mg and dissolved in ethanol to 10 mL, with tripplecate experiment.…”

“…Absorbance was measured on wavelength 759 nm using UV-visible spectrophotometer. Absorption sample calculated based on equality regression standard of gallic acid to produced total phenolic content as percentage equivalent of gallic acid with w/w (% w/w GAE) [19].…”

Development of Minimum Competency Assessment (AKM)-Based Exercise Books to Improve Students' Literacy and Numeracy Skills at Sdn Janti 02 Sidoarjo

“…Berdasarkan penelitian terdahulu yang dilakukan oleh (Wulandari et al, 2019) bahwa pemahaman siswa dalam hal literasi numerasi masih rendah, hal tersebut ditunjukkan oleh hasil tes yang belum mencapai 50 % dari keseluruhan siswa, sehingga perlu banyak diperkenalkan soal-soal dengan model AKM kepada siswa. Menurut (Juniarni et al, 2021)untuk meningkatkan kemampuan matematika siswa hendaknya guru menyesuaikan pembelajaran di kelas yang mampu menstimulus kemampuan literasi matematisnya.…”