scholarly journals The Influence of Strata on the Nutrient Recycling within a Tropical Certified Organic Coffee Production System

ISRN Agronomy ◽  
2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
F. Mamani-Pati ◽  
D. E. Clay ◽  
S. A. Clay ◽  
H. Smeltekop ◽  
M. A. Yujra-Callata
Keyword(s):  
Coffea Arabica ◽  
Nutrient Recycling ◽  
Coffee Bean ◽  
Coffee Production ◽  
Coffee Plantations ◽  
Green Coffee Beans ◽  
Coffee Beans ◽  
Certified Organic ◽  
Middle Strata ◽  
Organic Coffee

In tropical Bolivia coffee plantations, the plant community can be separated into high (trees), middle (coffee), and low (weed) strata. Understanding the importance of each stratum is critical for improving the sustainability of the system. The objective of this study was to determine the importance of strata on nutrient recycling. Litter falls from the upper and middle strata were collected monthly using cone-shaped traps and divided by species into leaves, branches, flowers, and fruits. Dry biomass additions to the soil from high and middle strata totaled 12,655 kg (ha yr)−1 annually. About 76% of the biomass was provided by plants of the genus Inga (I. adenophylla and I. oerstediana). The middle stratum (Coffea arabica L.) provided 24% litterfall biomass. This stratum also produced 1,800 kg coffee bean per ha (12% moisture) which sold for $2.94 kg−1. In the lower stratum, Oxalis mollissima returned 36 kg N ha−1, while Solanum nodiflorum returned 49 kg K ha−1, and Urtica sp. returned 18 kg Ca ha−1. The nutrients recycled through plants in three strata exceeded the amount of nutrients removed in green coffee beans.

Social Entrepreneurship and Arabica Coffee Production in the Northern Philippines: Navigating Opportunities and Constraints

2021 ◽  
Vol 80 (1) ◽  
pp. 72-82
Author(s):  
B. Lynne Milgram
Keyword(s):  
Social Entrepreneurship ◽  
Private Investment ◽  
Social Entrepreneurs ◽  
Coffee Production ◽  
Arabica Coffee ◽  
Green Coffee Beans ◽  
Start Up ◽  
Alternative Approach ◽  
Coffee Beans ◽  
Private Government

Private, government, and corporate sectors increasingly seek to mitigate the precarious economic and environmental conditions their businesses have caused. Given the shortcomings of conventional approaches to achieve meaningful social change, social entrepreneurship has emerged as an alternative approach to answer this call. Combining business, private investment, and social movement models, social entrepreneurs work collaboratively with communities to augment peoples’ livelihood and their social security. This article draws on social entrepreneurship scholarship to analyze entrepreneurs’ initiatives in the northern Philippines’ emergent specialty Arabica coffee industry. I explore the extent to which entrepreneurs can operationalize opportunities and mitigate constraints as they expand from their small start-up premises while maintaining their social mandate. Given that current demand for premium green coffee beans outstrips supply, entrepreneurs may find themselves in competition with one another. This situation coupled with the Philippine government’s inability to secure peoples’ subsistence needs means that farmers may betray their allegiance to the entrepreneurs who supported them. I ask: do social entrepreneurs’ efforts simply alleviate symptoms rather than address root causes of inequality? Entrepreneurs’ efforts to date have led to positive industry outcomes; this suggests that pursuing such cross-sector advocacy can potentially curtail challenges to enterprise sustainability.

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

scholarly journals Carbon Isotope Discrimination Correlates with Bean Yield of Diverse Coffee Seedling Populations

HortScience ◽  
1991 ◽  
Vol 26 (11) ◽  
pp. 1413-1414 ◽  
Author(s):  
F.C. Meinzer ◽  
J.L. Ingamells ◽  
C. Crisosto
Keyword(s):  
Carbon Isotope ◽  
Coffea Arabica ◽  
Carbon Isotope Discrimination ◽  
Green Coffee ◽  
Substantial Variation ◽  
Isotope Discrimination ◽  
Green Coffee Beans ◽  
Coffee Beans ◽  
Bean Yield ◽  
Superior Genotypes

Foliar C isotope discrimination (Δ) and yield of green coffee (Coffea arabica L.) beans were evaluated for seedling populations from 14 diverse coffee cultivars growing in Hawaii. A was negatively correlated with yield of green coffee beans. The 2% variation in A observed in leaves sampled about 2 months after completion of the first harvest corresponded to a 3-fold variation in yield. Substantial variation in A exists among coffee cultivars, and foliar A analyses show promise as a means of selecting superior genotypes of long-lived woody crops.

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 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.

Incidence of microflora and of ochratoxin A in green coffee beans (Coffea arabica)

2003 ◽  
Vol 20 (12) ◽  
pp. 1127-1131 ◽  
Author(s):  
M. L. Martins ◽  
H. M. Martins ◽  
A. Gimeno
Keyword(s):  
Ochratoxin A ◽  
Coffea Arabica ◽  
Green Coffee ◽  
Green Coffee Beans ◽  
Coffee Beans

scholarly journals ANALYTICAL METHOD DEVELOPMENT AND VALIDATION FOR THE DETERMINATION OF CAFFEINE IN GREEN COFFEE BEANS (COFFEA ARABICA L.) FROM THREE DISTRICTS OF WEST JAVA, INDONESIA BY HIGH PERFORMANCE LIQUID CHROMATOGRAPHY

2018 ◽  
Vol 10 (6) ◽  
pp. 103
Author(s):  
Febrina Amelia Saputri ◽  
Muchtaridi Muchtaridi
Keyword(s):  
Analytical Method ◽  
Coffea Arabica ◽  
Limit Of Detection ◽  
Hplc Method ◽  
Green Coffee ◽  
West Java ◽  
Green Coffee Beans ◽  
Coffee Beans ◽  
Coffea Arabica L

Objective: To develop and validate a simple, accurate, and precise HPLC method for the determination of caffeine in green coffee beans (Coffea arabica L.) from three districts of West Java, Indonesia.Methods: The analytical method was conducted using Enduro C-18 (250 x 4.6 mm) column with methanol: water (37: 63) as a mobile phase, the flow rate was 1.0 ml/min, and the detector wavelength was set at 274 nm. The selectivity, linearity, limit of detection (LOD), limit of quantification (LOQ), accuracy, precision, and system suitability testing were evaluated as the parameters of validation.Results: The retention time of caffeine was 6.36 min. % RSD for precision was 0.192. The linearity of the method was obtained using a concentration range of 1-200 ppm with the correlation coefficient of 0.998. The limit of detection was 9 ppm and the limit of quantitation was 28 ppm. The accuracy was in between 90.723%-102.853%. Caffeine levels from Garut, Pangalengan, and Tasikmalaya were 1.454 ± 0.004%, 1.574 ± 0.082%, and 2.280 ± 0.004%.Conclusion: The proposed HPLC method meets the acceptance criteria of validation parameters and can be applied for routine analysis.

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.

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.

Sign in / Sign up

Export Citation Format

Share Document