scholarly journals The Effect of Various Processing Methods on Ease of Removal of More than Half the Silver Skin from Green Coffee Beans

1969 ◽  
Vol 43 (2) ◽  
pp. 128-131
Author(s):  
D. S. Boyce
Keyword(s):  
Coffee Bean ◽  
Green Coffee ◽  
Probability Level ◽  
Natural Fermentation ◽  
Green Coffee Beans ◽  
Rotary Drier ◽  
Coffee Beans ◽  
Significant Difference ◽  
Main Effects ◽  
Green Coffee Bean

It has been shown that the methods utilized to process coffee cherries to dry coffee parchment affect to a considerable extent the ease with which the silver skin may be removed from the green coffee bean subsequently. Natural fermentation is significantly more effective at the 0.01 probability level in producing a sample with an easily removable silver skin than mechanical demucilaging with the Hess machine. Artificial drying produces a sample from which the silver skin can be more easily removed than natural drying at the 0.05 probability level. Furthermore, there was significance at the 0.01 probability level when the interaction between the two main effects of drying and demucilaging were considered. In considering the interaction of the two main effects it was found that natural fermentation combined with artificial (rotary-drier) drying produced the most favorable results. It was significantly greater than any of the other three possible combinations at the 0.01-percent probability level and there was no significant difference between the latter three. This lack of significance may be attributed, in part, to possible negative interaction between the two main effects, that is, in certain combinations the two main effects may have the effect of causing the silver skin to adhere tenaciously to the bean.

scholarly journals The Effect of Orlistat, Green Coffee Bean Extract, and Its Combinations on Lipid Profi le and Adiponectin Levels

Jurnal NERS ◽  
2017 ◽  
Vol 9 (1) ◽  
pp. 26 ◽  
Author(s):  
Joko Setyono ◽  
Dwi Adi Nugroho ◽  
Mustofa Mustofa ◽  
Saryono Saryono
Keyword(s):  
Chlorogenic Acid ◽  
Water Extract ◽  
Ethanol Extract ◽  
Control Group ◽  
Coffee Bean ◽  
Green Coffee ◽  
Green Coffee Beans ◽  
Coffee Beans ◽  
Significant Difference ◽  
Obese Rats

Introduction: Obesity prevalence is estimated increases, reached 19.1% of the population aged 15 years and over. This study aimed to determine the differences of the anti- obesity effect of orlistat, an extract of green coffee beans (Coffea canephora robusta), and its combination to the adiponectin levels and lipid profi le. Method: This research was true experimental post -test only with control group design with completely randomized design (CRD). Experimental animals (Rattus novergicus) were divided into 6 group, group 1 ( negative control ), group 2 ( positive control ), group 3 was group of obese rats fed orlistat dose of 15.9 mg/kg, group 4 was the group of obese rats were fed ethanol extract of green coffee beans dose of 400 mg/kg, group 5 was the group of obese rats were given water extract of green coffee beans dose of 400 mg/kg, and group 6 was group of obese rats were fed a combination of orlistat dose of 15.9 mg/kgand ethanol extract of green coffee beans at a dose of 400 mg/kg. Lipid profi les and adiponectin levels were measured with a spectrophotometer at 500nm absorbance. The data were analyzed by one-way ANOVA, and then post hoc Least Significant Difference (LSD) with α = 0.05. Result: Ethanol extract of green coffee is more effi cient in lowering LDL cholesterol, increasing HDL cholesterol, and lowering the total cholesterol levels on HFD diet-induced mice, but there was no difference in lowering triglycerides . The combination of ethanol extract of green coffee with orlistat showedthe increasing of adiponectin levels were highest than the other treatment groups. Discussion: The ethanol extract of green coffee readily diffuses through the digestive tract epithelium. Green coffee contains chlorogenic acid active compounds that can increase the body’s metabolism, increase fatty acid oxidation, reduce levels of triglycerides in the liver, and working to inhibit lipase and amylase pancreaticenzymes. In addition to chlorogenic acid, polyphenol content in coffee is also potentially reduce visceral fat accumulation. Preparations extract by ethanol allows the absorption process is done effi ciently and quickly.Keywords: obesity, orlistat, greencoffee, lipid profi le, adiponectin

Incidence of Toxigenic and Other Molds in Green Coffee Beans

1983 ◽  
Vol 46 (11) ◽  
pp. 969-973 ◽  
Author(s):  
PHILIP B. MISLIVEC ◽  
VERNEAL R. BRUCE ◽  
REGINA GIBSON
Keyword(s):  
South America ◽  
South American ◽  
Coffee Bean ◽  
Green Coffee ◽  
African Countries ◽  
Surface Disinfection ◽  
Green Coffee Beans ◽  
Coffee Beans ◽  
Before And After ◽  
Green Coffee Bean

The mold flora of 944 green coffee bean samples from 31 coffee-producing countries was determined before and after surface disinfection with 5% NaOCl. Molds were detected on 99.1 % of 47,200 beans not surface-disinfected and in 47.9% of 47,200 disinfected beans. Although the percentage of differences in occurrence of mold before disinfection was minimal (93.4 to 100%) on a country-by-country basis, after disinfection the beans from Asiatic and African countries showed more internal invasion (80.5%) than those from Central and South America (49.4%). Aspergillus spp., which dominated the mold flora of 944 samples before and after disinfection, included the toxigenic A. ochraceus, A. flavus and A. versicolor as well as A. niger, A. tamarii, A. wentii and species of the A. glaucus group. The genus Penicillium, including the toxigenic P. cyclopium, P. citrinum and P. expansum, was detected regularly, although its occurrence was substantially lower than that of the aspergilli, especially after surface disinfection. The rare detection of Alternaria and Fusarium indicated that toxigenic species of these genera do not readily invade green coffee beans. A. flavus and A. tamarii were prevalent in Central and South American beans, whereas other aspergilli were prevalent in Asiatic and African beans. The penicillia were prevalent in Central and South American beans.

scholarly journals Green coffee bean seed and their role in antioxidant–A review

2020 ◽  
Vol 11 (1) ◽  
pp. 233-240 ◽  
Author(s):  
Bothiraj K V ◽  
Murugan ◽  
Vanitha V
Keyword(s):  
Antioxidant Activities ◽  
Coffee Bean ◽  
Green Coffee ◽  
Anticancer Activities ◽  
Caffeoylquinic Acids ◽  
Antitumor Property ◽  
Green Coffee Beans ◽  
Coffee Beans ◽  
Phenolic Constituents ◽  
Green Coffee Bean

All around the world, Coffee place an important position in the beverages. It contains phenolic acid as well as polyphenols. It has the property of antioxidant; mood enhances mood, and also increases alertness, reduces weight, efficiency against hypertension, and antitumor property because of its polyphenols and phenolic constituents. Chlorogenic acids (CGA) are the main components found in the fraction of phenols from green coffee beans. CGA has several therapeutic properties, which include antioxidant activities and also has hepatoprotective, hypoglycemic, and antiviral properties.  Several essential compounds found in CGA in green coffee beans are caffeoylquinic acids, caffeoylquinic acids, feruloyl quinic acids, p-coumaroylquinic acids, and quinic acid. Therefore, this review highlighted the health benefits and anticancer activities of Green coffee bean.

scholarly journals Changes Of Some Engineering Properties Of Coffee Beans Due To Roasting Process

2020 ◽  
Vol 8 (1) ◽  
Author(s):  
Ashri Indriati ◽  
Dadang D Hidayat ◽  
Cecep E Andriansyah ◽  
Ari Rahayuningtyas ◽  
Arie Sudaryanto
Keyword(s):  
Weight Loss ◽  
Moisture Content ◽  
Volume Change ◽  
Engineering Properties ◽  
Coffee Bean ◽  
Green Coffee ◽  
Robusta Coffee ◽  
Coffee Beans ◽  
Roasting Process ◽  
Green Coffee Bean

The changes in physical, mechanical, and colours after roasting in two-level were investigated. Aims of this study were to evaluate changes in the physical, mechanical, and colours due to the roasting process of the Arabica and Robusta coffee bean grown in Cisalak Sub-District, Subang District-West Java. Results of analysis determined that the roasting process resulted in decreasing the moisture content of green coffee bean from 13.8% to 6,54% of first-level roasted bean and 6.24 of the second-level roasted bean, while that of robusta decreased from  11.22% to 7.56 and 6.12%. First-level roasting was categorised as a light roast, while the second-level was a medium roast. The Roast Weight Loss of arabica and robusta from green to light roast bean were 19.45 % and 16,24%, respectively, and that to medium roast bean was 26.20% and 22.37%, respectively. The roast volume change of arabica and robusta from green to light roast bean were 50.55% and 44.30 % respectively, and that to medium roast bean were 54.65% and 55.92 % respectively. The total colour differences between green with light and medium roast bean of arabica were 6.39 and 2.52, while that of robusta were 6.19 and 2.49, respectively.

scholarly journals Application of colour, shape, and texture parameters for classifying the defect of Gayo Arabica green coffee bean using computer vision

2022 ◽  
Vol 951 (1) ◽  
pp. 012097
Author(s):  
A Maghfirah ◽  
I S Nasution
Keyword(s):  
Computer Vision ◽  
Intelligent System ◽  
Training Data ◽  
National Standard ◽  
Support Vector ◽  
Coffee Bean ◽  
Green Coffee ◽  
Coffee Beans ◽  
Green Coffee Bean

Abstract Coffee is the most important commodity in the trading industry. Determination of the quality of coffee is still done manually so that it cannot separate good quality coffee beans with bad quality coffee beans. This research conducted the development of a visual-based intelligent system using computer vision to be able to classify the quality of rice coffee based on the Indonesian National Standard (SNI). The models used in the study are the K-Nearest Neighbour (K-NN) method and the Support Vector Machine (SVM) method with 13 parameters used such as; area, contrast, energy, correlation, homogeneity, circularity, perimeter, and colour index R(red), G (green), B (blue), L*, a* and b*. A total of 1200 Arabica green coffee bean captured using Kinect V2 camera with training data of 1000 samples and testing data of 200 samples.

scholarly journals Quality and Defect Inspection of Green Coffee Beans Using a Computer Vision System

2019 ◽  
Vol 9 (19) ◽  
pp. 4195 ◽  
Author(s):  
García ◽  
Candelo-Becerra ◽  
Hoyos
Keyword(s):  
Image Processing ◽  
Nearest Neighbor ◽  
Vision System ◽  
Coffee Bean ◽  
Green Coffee ◽  
K Nearest Neighbor ◽  
Green Coffee Beans ◽  
Coffee Beans ◽  
Supervised Learning Algorithms ◽  
K Nearest Neighbor Algorithm

There is an increased industry demand for efficient and safe methods to select the best-quality coffee beans for a demanding market. Color, morphology, shape and size are important factors that help identify the best quality beans; however, conventional techniques based on visual and/or mechanical inspection are not sufficient to meet the requirements. Therefore, this paper presents an image processing and machine learning technique integrated with an Arduino Mega board, to evaluate those four important factors when selecting best-quality green coffee beans. For this purpose, the k-nearest neighbor algorithm is used to determine the quality of coffee beans and their corresponding defect types. The system consists of logical processes, image processing and the supervised learning algorithms that were programmed with MATLAB and then burned into the Arduino board. The results showed this method has a high effectiveness in classifying each single green coffee bean by identifying its main visual characteristics, and the system can handle several coffee beans present in a single image. Statistical analysis shows the process can identify defects and quality with high accuracy. The artificial vision method was helpful for the selection of quality coffee beans and may be useful to increase production, reduce production time and improve quality control.

scholarly journals Investigation of Physical and Sensory Properties of Ethiopian Specialty Dry Processed Green Coffee Beans

2020 ◽  
Vol 24 (1) ◽  
pp. 39-48
Author(s):  
Yishak Worku Wondimkun ◽  
Shimelis Admassu Emire ◽  
Tarekegn Berhanu Esho
Keyword(s):  
Physical Properties ◽  
Process Optimization ◽  
Sensory Properties ◽  
Coffee Bean ◽  
Green Coffee ◽  
Green Coffee Beans ◽  
Linear Dimensions ◽  
Standard Procedures ◽  
Coffee Beans ◽  
Relationship Of

AbstractEthiopia is known for its specialty Arabica coffees affected by mix-up. Physical and sensory properties of dry processed green coffee beans have been reported for the influence on the sensorial quality and coffee process optimization. The aim of this study was to investigate physical and sensory properties of sixteen varieties and to determine relationship of attributes. Physical properties of coffee beans were taken by measuring linear dimensions, densities and weight. Moreover, professional cuppers were analyzed sensory properties by using standard procedures. In this study, the longest (10.40 mm), the widest (6.82 mm) and the thickest (4.48 mm) varieties were Odicha, Feyate and Challa, respectively whereas the shortest (8.28 mm), narrowest (5.59 mm) and thinnest (3.52 mm) were 74110, Mocha and Bultum, respectively. The shape & make value of variety Bultum was “fair good” whereas variety Feyate was “very good”. Furthermore, the results of “shape & make” were significantly correlated with measured physical properties. The results indicate that most physical and sensory properties of coffee varieties have significant (P ≤ 0.05 differences. These properties were influenced by growing regions and variety difference. The outcome of this study can be used for coffee bean characterization and process optimization to improve beverage quality.

Metals in green coffee beans from major coffee-growing regions of Ethiopia

2019 ◽  
Author(s):  
Chem Int
Keyword(s):  
Addis Ababa ◽  
Pearson Correlation ◽  
Capital City ◽  
Green Coffee ◽  
Mineral Contents ◽  
Flame Atomic Absorption ◽  
Green Coffee Beans ◽  
External Calibration Curve ◽  
Coffee Beans ◽  
Significant Difference

The metal contents of green coffee beans cultivated in major coffee growing zones of Ethiopia (Wollega, Sidamo, Harar, Bench Maji and Kafa) have been determined in representative samples of the five coffee varieties collected from Coffee Quality Inspection and Liquoring Center located in Addis Ababa, the capital city of Ethiopia. Different sample preparation procedures were tested by varying reagent volumes and types, digestion time, digestion temperature and amount of the sample to decompose the green coffee beans and solubilize the metals. The optimal procedure required 4 h to completely digest 0.5 g of green coffee beans with 5 mL HNO3 (70%) and 1.5 mL HClO4 (70%) at 270 oC. Concentrations of metals (Ca, Cd, Cr, Co, Cu, Fe, K, Mg, Mn, Ni, Pb and Zn) were determined by flame atomic absorption spectrometer employing a four point external calibration curve. The accuracy of the optimized procedure was evaluated by analyzing sample digests spiked with standard solutions. Recoveries of the spiked samples varied from 90 to 110% in green coffee beans. The metals levels observed in green coffee beans are comparable to literature reports. Cd was not detected in any of the five samples while Pb was detected at trace level in only one of the five samples. This indicated that the Ethiopian green coffee beans are free from the toxic metals. The Pearson correlation coefficients indicated strong to medium positive or negative correlation among the metals in the green coffee beans. The analysis of variance results at 95% confidence level suggested that there were significant difference in the concentrations of all the metals except K between the five sampling areas. Thus, this study has revealed variation of metal composition of green coffee beans with the geographical origin of the coffee verities. The variation in composition among coffee sample might be due the differences in mineral contents of the corresponding soils.

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