Determination of the geographical origin of green coffee beans using NIR spectroscopy and multivariate data analysis

Giraudo, Alessandro; Grassi, Silvia; Savorani, Francesco; Gavoci, Gentian; Casiraghi, E.; Geobaldo, Francesco

doi:10.1016/j.foodcont.2018.12.033

Cited by 123 publications

(68 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Menurut Rendon et al (2014) kopi arabika memiliki flavor dan rasa yang lebih disukai oleh para konsumen dibandingkan kopi robusta. Tingginya kualitas citarasa kopi arabika menyebabkan nilai komersial kopi tersebut juga tinggi, hal ini memungkinkan terjadinya pencampuran antara kopi arabika dan robusta (Giraudo et al, 2019) dalam perdagangan. Pencampuran dapat terjadi baik pada biji kopi (sebelum disangrai) maupun kopi yang telah disangrai.…”

Section: Pendahuluanunclassified

“…Hasil analisis PCA yang dilakukan ditampilkan dalam bentuk score plot dan loading plot. Score plot PCA digunakan untuk melihat pemisahan sampel biji kopi, sedangkan loading plot PCA digunakan untuk melihat penyebaran karakteristik kimia yang menentukan pemisahan sampel tersebut (Giraudo et al, 2019;Monakhova et al, 2015).…”

Section: Pemetaan Karakteristik Kimia Biji Kopi Arabika Gayo Dan Robuunclassified

See 1 more Smart Citation

Pemetaan Karakteristik Kimia Biji Kopi Arabika Gayo Dan Robusta Gayo

Saputri

Lioe

Wijaya

2020

jtip

View full text Add to dashboard Cite

The distinctive aroma and taste of roasted coffee can b e due to varietal differences in green coffee b eans. The purpose of this research was to map the chemical characteristics of green coffee b eans of Gayo arab ica and Gayo rob usta using principal component analysis (PCA) approach. Other analyses include pH using pH meter, total fats b y Soxhlet method, total ash b y gravimetric method, total protein b y Kjeldahl method, total carb ohydrates b y difference, total solub le solids (TSS) b y refractometer, organic acids composition b y HPLC-UV/Vis, and total amino acids composition b y UHPLC-PDAD. Six green coffee b ean samples of Gayo arab ica and Gayo rob usta from different locations in Gayo, Aceh, as well as samples of arab ica and rob usta coffee b eans each from plantation in West Java, Central Java and East Java (as comparators) were used in this study. The results showed the chemical characteristics of Gayo arab ica and Gayo rob usta could b e mapped b y PCA b ased on the concentrations of fats, organic acids and carb ohydrates. The organic acid composition of Gayo arab ica was associated with malic acid, succinic acid and citric acid, while Gayo rob usta to acetic acid. The organic acids as well as TSS of the coffee b eans could map Gayo arab ica separately from Java arab ica. Gayo arab ica had higher organic acids, whereas Java arab ica had higher TSS. Gayo rob usta were characterized b y higher fats, ash and total amino acids, b ut lower TSS than Java rob usta. This study suggested the distinct characteristics of Gayo coffee b eans to their corresponding coffee b eans from Java.

show abstract

Section: Pendahuluanunclassified

Section: Pemetaan Karakteristik Kimia Biji Kopi Arabika Gayo Dan Robuunclassified

Pemetaan Karakteristik Kimia Biji Kopi Arabika Gayo Dan Robusta Gayo

Saputri

Lioe

Wijaya

2020

jtip

View full text Add to dashboard Cite

show abstract

“…NIR spectroscopy is characterized by speed, reliability, simplicity, security, low operation cost, minimum sample processing, low instrumental maintenance, allowing various analyses simultaneously and not requiring the use of chemicals . This technique has already proven useful for the prediction of several properties in coffee samples and has been applied in the determination of antioxidants, caffeine, cafestol and kahweol, roasting degree prediction, chemical composition of defective beans, sensory characteristics and geographical origin . In this context, the objective of the work presented here was to evaluate the potential of NIR spectroscopy and spectral pre‐processing methods associated with partial least squares regression (PLS‐R) in determining the pH and acidity of green coffee samples.…”

Section: Introductionmentioning

confidence: 99%

Determination of pH and acidity in green coffee using near‐infrared spectroscopy and multivariate regression

et al. 2020

View full text Add to dashboard Cite

BACKGROUND Coffee is a raw material of global interest. Due to its relevance, this work evaluated the performance of calibration models constructed from spectral data obtained using near‐infrared spectroscopy (FT‐NIR) to determine the pH values and acidity in coffee beans in a practical and non‐destructive way. Partial least squares regression was used during the calibration and the cross‐validation to optimize the number of latent variables. The predictive capacity of the spectral pre‐processing methods was also accessed. RESULTS The results obtained showed that the best methods of pre‐processing were the first derivative for the pH variable and the standard normal variate for the acidity, which produced models with correlations of 0.78 and 0.92, ratios of prediction to deviation of 2.061 and 2.966 and biases of −0.00011 and −0.152 to test set validation, respectively. The average errors between predicted and experimental values were lower than 7%. CONCLUSIONS FT‐NIR was successfully applied to predict properties related to the quality of coffee. The method was demonstrated to be a fast and non‐destructive tool which allows the rapid inline evaluation of samples facilitating industrial and commercial processing. © 2020 Society of Chemical Industry

show abstract

“…Near-infrared (NIR) spectroscopy may well be an alternative to those other analysis methods, since it is cheaper than other instrumental techniques and allows for a nondestructive, simple, and fast analysis [4]. NIR spectroscopy combined with multivariate data analysis (chemometrics) have recently been demonstrated to be a solution of process analytical technology in the food industry [5].…”

Section: Introductionmentioning

confidence: 99%

Monitoring the Processing of Dry Fermented Sausages with a Portable NIRS Device

González‐Mohíno

Pérez‐Palacios

Antequera

et al. 2020

Foods

Self Cite

View full text Add to dashboard Cite

This work studies the ability of a MicroNIR (VIAVI, Santa Rosa, CA) device to monitor the dry fermented sausage process with the use of multivariate data analysis. Thirty sausages were made and subjected to dry fermentation, which was divided into four main stages. Physicochemical (weight lost, pH, moisture content, water activity, color, hardness, and thiobarbiruric reactive substances analysis) and sensory (quantitative descriptive analysis) characterizations of samples on different steps of the ripening process were performed. Near-infrared (NIR) spectra (950–1650 nm) were taken throughout the process at three points of the samples. Physicochemical data were explored by distance to K-Nearest Neighbor (K-NN) cluster analysis, while NIR spectra were studied by partial least square–discriminant analysis; before these models, Principal Component Analysis (PCA) was performed in both databases. The results of multivariate data analysis showed the ability to monitor and classify the different stages of ripening process (mainly the fermentation and drying steps). This study showed that a portable NIR device (MicroNIR) is a nondestructive, simple, noninvasive, fast, and cost-effective tool with the ability to monitor the dry fermented sausage processing and to classify samples as a function of the stage, constituting a feasible decision method for sausages to progress to the following processing stage.

show abstract

Determination of the geographical origin of green coffee beans using NIR spectroscopy and multivariate data analysis

Cited by 123 publications

References 41 publications

Pemetaan Karakteristik Kimia Biji Kopi Arabika Gayo Dan Robusta Gayo

Pemetaan Karakteristik Kimia Biji Kopi Arabika Gayo Dan Robusta Gayo

Determination of pH and acidity in green coffee using near‐infrared spectroscopy and multivariate regression

Monitoring the Processing of Dry Fermented Sausages with a Portable NIRS Device

Contact Info

Product

Resources

About