Fitri Amalia1, Pingkan Aditiawati2, Sastia Prama Putri3,4,5, Eiichiro Fukusaki1,6,7. 1. Department of Biotechnology, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871, Japan. 2. School of Life Sciences and Technology, Institut Teknologi Bandung, Jl. Ganesha No.10, Lb. Siliwangi, Coblong, Kota Bandung, Jawa Barat, 40132, Indonesia. 3. Department of Biotechnology, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871, Japan. sastia_putri@bio.eng.osaka-u.ac.jp. 4. School of Life Sciences and Technology, Institut Teknologi Bandung, Jl. Ganesha No.10, Lb. Siliwangi, Coblong, Kota Bandung, Jawa Barat, 40132, Indonesia. sastia_putri@bio.eng.osaka-u.ac.jp. 5. Industrial Biotechnology Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871, Japan. sastia_putri@bio.eng.osaka-u.ac.jp. 6. Industrial Biotechnology Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871, Japan. 7. Osaka University Shimadzu Omics Innovation Research Laboratories, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871, Japan.
Abstract
INTRODUCTION: Coffee is a popular beverage because of its pleasant aroma and distinctive flavor. The flavor of coffee results from chemical transformations influenced by various intrinsic and extrinsic factors, including altitude, geographical origin, and postharvest processing. Despite is the importance of grading coffee quality, there is no report on the dominant factor that influences the metabolomic profile of green coffee beans and the correlated metabolites for each factor. OBJECTIVE: This study investigated the total metabolite profile of coffees from different altitudes and coffees subjected to different postharvest processing. METHOD: Arabica green coffee beans obtained from different geographical origins and different altitudes (400 and 800 m) and produced by different postharvest processes (dry, honey, and washed process) were used in this study. Coffee samples obtained from altitudes of 400-1600 m above sea level from various origins that were produced by the washed method were used for further study with regard to altitudes. Samples were subjected to gas chromatography/mass spectrometry (GC/MS) analysis and visualized using principal component analysis (PCA) and orthogonal partial least squares (OPLS) regression analysis. RESULTS: The PCA results showed sample separation based on postharvest processing in PC1 and sample separation based on altitude in PC2. A clear separation between samples from different altitudes was observed if the samples were subjected to the same postharvest processing method, and the samples were of the same origin. Based on this result, OPLS analysis was conducted using coffee samples obtained from various altitudes with the same postharvest processing. An OPLS model using altitude as a response variable and 79 metabolites annotated from the GC/MS analysis as an explanatory variable was constructed with good R2 and Q2 values. CONCLUSION: Postharvest processing was found to be the dominant factor affecting coffee metabolite composition; this was followed by geographical origin and altitude. The metabolites glutamic acid and galactinol were associated with the washed and honey process, while glycine, lysine, sorbose, fructose, glyceric acid, and glycolic acid were associated with the dry process. Two metabolites with high variable influence on projection scores in the OPLS model for altitude were inositol and serotonin, which showed positive and negative correlations, respectively. This is the first study to report characteristic coffee metabolites obtained from different altitudes.
INTRODUCTION: Coffee is a popular beverage because of its pleasant aroma and distinctive flavor. The flavor of coffee results from chemical transformations influenced by various intrinsic and extrinsic factors, including altitude, geographical origin, and postharvest processing. Despite is the importance of grading coffee quality, there is no report on the dominant factor that influences the metabolomic profile of green coffee beans and the correlated metabolites for each factor. OBJECTIVE: This study investigated the total metabolite profile of coffees from different altitudes and coffees subjected to different postharvest processing. METHOD: Arabica green coffee beans obtained from different geographical origins and different altitudes (400 and 800 m) and produced by different postharvest processes (dry, honey, and washed process) were used in this study. Coffee samples obtained from altitudes of 400-1600 m above sea level from various origins that were produced by the washed method were used for further study with regard to altitudes. Samples were subjected to gas chromatography/mass spectrometry (GC/MS) analysis and visualized using principal component analysis (PCA) and orthogonal partial least squares (OPLS) regression analysis. RESULTS: The PCA results showed sample separation based on postharvest processing in PC1 and sample separation based on altitude in PC2. A clear separation between samples from different altitudes was observed if the samples were subjected to the same postharvest processing method, and the samples were of the same origin. Based on this result, OPLS analysis was conducted using coffee samples obtained from various altitudes with the same postharvest processing. An OPLS model using altitude as a response variable and 79 metabolites annotated from the GC/MS analysis as an explanatory variable was constructed with good R2 and Q2 values. CONCLUSION: Postharvest processing was found to be the dominant factor affecting coffee metabolite composition; this was followed by geographical origin and altitude. The metabolites glutamic acid and galactinol were associated with the washed and honey process, while glycine, lysine, sorbose, fructose, glyceric acid, and glycolic acid were associated with the dry process. Two metabolites with high variable influence on projection scores in the OPLS model for altitude were inositol and serotonin, which showed positive and negative correlations, respectively. This is the first study to report characteristic coffee metabolites obtained from different altitudes.
Authors: Mayara de Souza Gois Barbosa; Maria Brígida Dos Santos Scholz; Cíntia Sorane Good Kitzberger; Marta de Toledo Benassi Journal: Food Chem Date: 2019-04-20 Impact factor: 7.514
Authors: Gilberto V de Melo Pereira; Dão P de Carvalho Neto; Antonio I Magalhães Júnior; Zulma S Vásquez; Adriane B P Medeiros; Luciana P S Vandenberghe; Carlos R Soccol Journal: Food Chem Date: 2018-08-17 Impact factor: 7.514