Defective Beans Research Articles

Preparation of mesoporous activated carbon from defective coffee beans for adsorption of fresh whey proteins

Whey protein has high biological value and functional properties. Therefore, it is necessary to develop methods to recover this valuable protein and minimize the environmental impacts. Adsorptive processes using alternative adsorbents from agroindustrial waste increase the number of alternatives for adequate final disposal of the waste and add value. The aim of this study was to develop a mesoporous activated carbon (AC) from defective coffee beans (DCB) for the adsorption of fresh whey protein. The morphological structure of the adsorbent produced was characterized, and both Raman spectroscopy, FTIR and thermal analyses were performed; and the effect of pH on the adsorption capacity (q, mg g-1) was evaluated. The characterization showed that: the AC exhibited a porous size between 33 and 43 Å, corresponding to mesoporous materials; the crystallite size (La) of AC was estimated at 9.31 ± 0.14 nm; the highest adsorption capacity value (239.1781 mg g-1) was achieved at pH 2.5 and 25ºC; and the point of zero charge of the adsorbent was at pH 2.0. The pseudo first-order model fit best to the experimental results (R2 > 0.99) of whey protein adsorption onto activated carbon, and the Langmuir model was the most appropriate to represent the experimental data, with a maximum adsorption capacity of 378.4380 mg g-1, demonstrating the potential of AC obtained from DCB to adsorb fresh whey protein.

Renewable sources: applications in personal care formulations.

A global tendency for products considered environmentally sustainable, and ecologically obtained led the industry related to personal care formulations to fund the research and the development of personal care/cosmetics containing ingredients from natural resources. Furthermore, consumers are aware of environmental and sustainability issueans, thus not harming the environment represents a key consideration when developing a new cosmetic ingredient. In this study we review some examples of active ingredients or raw materials used in cosmetics/personal care/biomedical products that are coming from either through biotechnological systems, or as byproducts of several industries. A skin formulation containing biosynthetic actives, prepared by us and the study regarding its dermocosmetic properties are also described. The need for the standardization processes, the safety assessment tools, the improvement of the exploitation methods of these renewable sources in order the production to be ecologically and economically better are also discussed.

Deep-Learning-Based Defective Bean Inspection with GAN-Structured Automated Labeled Data Augmentation in Coffee Industry

In the production process from green beans to coffee bean packages, the defective bean removal (or in short, defect removal) is one of most labor-consuming stages, and many companies investigate the automation of this stage for minimizing human efforts. In this paper, we propose a deep-learning-based defective bean inspection scheme (DL-DBIS), together with a GAN (generative-adversarial network)-structured automated labeled data augmentation method (GALDAM) for enhancing the proposed scheme, so that the automation degree of bean removal with robotic arms can be further improved for coffee industries. The proposed scheme is aimed at providing an effective model to a deep-learning-based object detection module for accurately identifying defects among dense beans. The proposed GALDAM can be used to greatly reduce labor costs, since the data labeling is the most labor-intensive work in this sort of solutions. Our proposed scheme brings two main impacts to intelligent agriculture. First, our proposed scheme is can be easily adopted by industries as human effort in labeling coffee beans are minimized. The users can easily customize their own defective bean model without spending a great amount of time on labeling small and dense objects. Second, our scheme can inspect all classes of defective beans categorized by the SCAA (Specialty Coffee Association of America) at the same time and can be easily extended if more classes of defective beans are added. These two advantages increase the degree of automation in the coffee industry. The prototype of the proposed scheme was developed for studying integrated tests. Testing results of a case study reveal that the proposed scheme can efficiently and effectively generate models for identifying defective beans with accuracy and precision values up to 80 % .

Characterization of volatile carbonyl compounds in defective green coffee beans using a fan assisted extraction process

In this work, the characterization of volatile carbonyl compounds profiles in healthy and defective green coffee beans was performed. The objective of this characterization was to identify carbonyl marker compounds related to the main bean defects of both arabica and robusta species (black, sour, immature and bored) in non-aged and aged beans. A simple and innovative procedure for volatile compounds extraction was developed, so that usual heating procedures that may adulterate samples' identity can be avoided. The coffee sample and an acceptor solution containing a carbonyl derivatizing reagent are placed inside a screw-cap flask featuring an inner electric fan. The efficiency of the volatile carbonyl compounds mass transfer could be increased due to the fan's operation. The experimental parameters, fan rotation speed, extraction period and sample mass were studied to improve the volatile compounds extraction before HPLC analysis. Defective green beans showed higher contents of some volatile carbonyl compounds than healthy green beans. The volatile carbonyl compounds profile obtained during the forced ageing assay revealed that butanal, benzaldehyde, 3-methylbutanal and hexanal were, consistently, found in higher amounts in both arabica and robusta defective beans, in comparison with healthy beans of the same lot.

An innovative multivariate strategy for HSI-NIR images to automatically detect defects in green coffee

In the present study, an advanced and original multivariate strategy for the processing of hyperspectral images in the near-infrared region is proposed to automatically detect physico-chemical defects in green coffee, which are similar one to each other by naked eye. An object-based approach for the characterization of individual beans, rather than single pixels, was adopted, calculating a series of descriptive parameters characterizing the distribution of scores on the lowest-order principal components. On such parameters, the k-nearest neighbors (k-NN) classification algorithm was applied and the predictive results on the test samples indicate that this approach is able not only to distinguish defective beans from non-defective ones, but also to differentiate the various types of defects. Hyperspectral imaging is demonstrated to be a valid alternative for the sorting of green beans – a crucial phase for coffee import/export.

Instant coffee with steamed PVA beans: Physical-chemical and sensory aspects

ABSTRACT Around 20% of Brazilian coffee production corresponds to defective beans (PVA), which decreases the quality of the coffee brews. Steam treatment has been reported as an alternative to improve the cup quality of coffee products. This research aimed to study the feasibility of using steamed Robusta PVA beans in instant coffee products. After the steam treatment (2 bar for 3 min), the Robusta PVA was dried, roasted, subjected to extraction in a pilot plant, and freeze-dried. The steamed and untreated Robusta PVA materials (raw, roasted, and instant coffees) and blends of instant Arabica coffee with PVA were characterized. The steamed Robusta PVA instant coffee presented 7.01 g caffeine and 8.74 g total chlorogenic acids in 100 g product. Instant coffee blends with 30% and 50% of steamed Robusta PVA in Arabica coffee were studied. A sensory difference between blends with steamed and untreated Robusta PVA was only perceived by the addition of 50% PVA. The blend with 50% of steamed coffee was preferred and well accepted (average grade of 7.9 on a 10-scale). The use of steamed Robusta PVA coffee (under mild steam treatment conditions, 2 bar/3 min) in instant coffee was viable, and it was obtained an instant coffee to be used in a blend with 50% of Arabica coffee with a good profile of bioactive compounds and sensory acceptance.

Prediction of black, immature and sour defective beans in coffee blends by using Laser-Induced Breakdown Spectroscopy.

One of the most important factors that interfere negatively in coffee global quality has been blends with defective beans, especially those called Black, Immature and Sour (BIS). The methods based on visual-manual estimation of defective beans have shown their inefficiency in coffee value chain for large-scale analysis. The lack of fast, accurate and robust analytical methods for BIS determination is still a research gap. Laser-Induced Breakdown Spectroscopy (LIBS) is a fast, low-cost and residue-free technique capable of performing multielemental determination and investigating organic composition of samples. In the present work, LIBS together with spectral processing and variable selection were evaluated to fit linear regression models for predicting BIS in blends. Models showed high capacity of prediction with RMSEP smaller than 3.8% and R2 higher than 80%. Most importantly, measurements are guided by chemical responses, which make LIBS-based methods less susceptible to the visual indistinguishability that occurs in manual inspections.

Effect of steam treatment on the profile of bioactive compounds and antioxidant activity of defective roasted coffee (Coffea canephora)

The article evaluated the influence of steam treatment (ST) on Coffea canephora defective beans regarding the profile of bioactive compounds and the antioxidant activity of roasted coffee. Defective crude beans were treated following a full factorial design 22 with the variables steam pressure (2–8 bar) and process time (3–29 min). The steamed coffees (SC) were dried, medium roasted and grounded. The ST affects (P < 0.05) the contents of caffeine, trigonelline, chlorogenic acids, melanoidins, cafestol and 16-O-methylcafestol. In general, the ST decrease the bioactive compounds and antioxidant activity compared to control sample (without ST). The profile of compounds for the SC roasted coffee depended on both ST and the subsequent roasting process. The bioactive compounds content in roasted SC were higher in conditions that combined a more drastic ST (8 bar/29 min) with a shorter roasting process, or a mild ST (2 bar/3 min) with a longer roasting process. ST with longer times and low pressures should be avoided to prevent the loss of bioactive compounds.

Effect of Reconditioning of Discrepant Cocoa on the Quality of Cocoa Beans

Reconditioning of cocoa beans which involves re-drying, sieving, sorting and re-bagging of cocoa beans is a very important process in the cocoa industry. The study was conducted to identify the fungi on and in cocoa beans before and after reconditioning. Defective cocoa beans namely, Damp, Wet, Not Thoroughly Dried (NTD), Mouldy beans and Good beans (control) were placed on water agar and Potato Dextrose Agar before and after reconditioning to isolate and identify external and internal fungi following the cut test technique. The result showed that a total of ten fungal species were isolated from the types of defective beans before and after reconditioning. These were; Absidia spp. Aspergillus flavus, A. niger, Fusarium spp, Mucor spp, Paecilomyces spp, Penicillium spp, Rhizopus spp. Syncephalastrum spp. and Trichoderma spp. However, after reconditioning the number of fungi reduced to five (5) that is Absidia spp, Aspergillus flavus, A. niger, Mucor spp and Rhizopus spp in the various treatments. The cut test also showed five internal fungi in the various treatments and these were Aspergillus flavus, A. niger, Mucor spp, Penicillium spp, and Rhizopus spp, High moisture content of the cocoa beans recorded before reconditioning was reduced to the acceptable safe moisture content of 7.5% or less after reconditionig. The FFA levels for the healthy beans (control) (0.77%), wet beans (1.64%), Damp beans (1.43%) and NTD beans (1.65%) were significantly lower (p&lt;0.05) than the FFA levels in the Mouldy beans (21.9%) after reconditioning. It can be concluded that reconditioning was capable of salvaging NTD beans, Damp beans and Wet beans with high moisture content from further spoilage.

Fraud investigation in commercial coffee by chromatography

Coffee is currently the second largest commodity on the world market today, and there is great concern about the quality of the beans exported from producer countries to Europe and USA. Practices such as using blends of different species and adding low-cost raw materials, such as chicory, corn, and soybean, impair the sensory and functional characteristics of the drink made from roasted and ground coffee beans. There is a need to adopt more efficient analytical methods than the microscopy technique currently used. The first chromatographic method used to determine fraud was reported in 1958. This method used paper chromatography to differentiate between coffee and chicory based on the free reducing sugars. As of the 1980s, different methods involving high-performance liquid chromatography and gas chromatography were developed in order to demonstrate geographic authenticity, distinction between species, occurrence of adulteration, and the presence of defective beans by determining the monosaccharides, oligosaccharides, tocopherols, fatty acids, volatiles, diterpenes, sterols, and phenolic substances, among others. As far as the authors know, there are no papers published in the literature that have compiled such an extensive set of information about these chromatographic methods as here. Over the last 2 years, there has been a trend to develop analytical methods for ultra-performance liquid chromatography coupled with tandem mass spectrometry to confirm fraud in coffee, due to high sensitivity and selectivity.

Qualitative carbonyl profile in coffee beans through GDME-HPLC-DAD-MS/MS for coffee preliminary characterization

In this work, an analytical methodology for volatile carbonyl compounds characterization in green and roasted coffee beans was developed. The methodology relied on a recent and simple sample preparation technique, gas diffusion microextraction for extraction of the samples' volatiles, followed HPLC-DAD-MS/MS analysis. The experimental conditions in terms of extraction temperature and extraction time were studied. A profile for carbonyl compounds was obtained for both arabica and robusta coffee species (green and roasted samples). Twenty-seven carbonyl compounds were identified and further discussed, in light of reported literature, with different coffee characteristics: coffee ageing, organoleptic impact, presence of defective beans, authenticity, human's health implication, post-harvest coffee processing and roasting. The applied methodology showed to be a powerful analytical tool to be used for coffee characterization as it measures marker compounds of different coffee characteristics.

Quantitative assessment of specific defects in roasted ground coffee via infrared-photoacoustic spectroscopy

Chemical analyses and sensory evaluation are the most applied methods for quality control of roasted and ground coffee (RG). However, faster alternatives would be highly valuable. Here, we applied infrared-photoacoustic spectroscopy (FTIR-PAS) on RG powder. Mixtures of specific defective beans were blended with healthy (defect-free) Coffea arabica and Coffea canephora bases in specific ratios, forming different classes of blends. Principal Component Analysis allowed predicting the amount/fraction and nature of the defects in blends while partial Least Squares Discriminant Analysis revealed similarities between blends (=samples). A successful predictive model was obtained using six classes of blends. The model could classify 100% of the samples into four classes. The specificities were higher than 0.9. Application of FTIR-PAS on RG coffee to characterize and classify blends has shown to be an accurate, easy, quick and “green” alternative to current methods.

Effects of Fruit Maturity, Bean Fermentation and Roasting Time on Physico-Chemical Characters of Robusta Coffee

&lt;em&gt;Robusta coffee is the most widely cultivated coffee in Indonesia. However, flavor quality of coffee is low due to improper harvesting and postharvest handling by farmers. Flavor quality mostly determined by fruit maturity level, fermentation and roasting time. The research aimed to investigate the effect of fruit maturity level, fermentation and roasting time on the physico-chemical characteristics of Robusta coffee. The research was conducted at Indonesian Industrial and Beverage Crops Research Institute (IIBCRI), from May to July 2017, used a completely ranndomized block design with 3 factors. The first factor was fruit maturity level (red and reddish yellow), second factor was bean fermentation (24 and 36 hours) and the third factor was roasting time (10 and 13 minutes). Physical quality covered percentage of live insects, moisture content, foreign materials and amount of defective beans. Chemical quality covered moisture content, ash, fat, protein, caffeine and acidity. The results showed that physical quality of fermented beans i.e. moisture content and amount of defective beans were affected by fruit maturity level and fermentation time, while foreign materials is affected by the interaction between these two factors. Chemical quality of coffee i.e. fat and caffeine content were affected by the interaction between fruit maturity level, and fermentation and roasting time. Water and protein content were affected by interaction between fruit maturity level and fermentation time, and interaction between fruit maturity level and roasting time. The ash content is affected by the roasting time, whereas pH is affected by fermentation time and roasting time.&lt;/em&gt;

Steam pressure treatment of defective Coffea canephora beans improves the volatile profile and sensory acceptance of roasted coffee blends

Between 15 and 20% of Brazilian coffee production corresponds to defective beans (PVA), which decreases the quality of the coffee brew. Steam treatment has been reported as an alternative to improve the volatile profile and cup quality of coffee. The aim of this study was to propose a steam treatment of defective Coffea canephora beans to improve the volatile profile of the roasted coffee. The sensory impacts of adding steamed coffee (SC) in Coffea arabica blends were evaluated. The steam treatments studied modified the volatile profile of roasted SCs, increasing the contents of acetoin, benzyl alcohol, maltol, 2,6-dimethylpyrazine, 2-furfurylthiol, and 5-methylfurfural and decreasing the contents of 4-ethylguaiacol, isovaleric acid, methional, 2,3-diethyl-5-methylpyrazine, and 3-methoxy-3-methylpyrazine. Among the evaluated parameters, the best condition to maximized the content of the volatiles with a potential positive impact and minimize those with a potential negative impact was 5bar/16min (SC 5). The thresholds of consumer rejection and of detection indicate that up to 30% SC 5 can be added to a high cup quality Coffea arabica coffee without perception or rejection of the coffee brew. A blend of 30% of SC 5 and 70% of Coffea arabica was well accepted.

Potential of Laser Induced Breakdown Spectroscopy for analyzing the quality of unroasted and ground coffee

Coffee is an important commodity and a very popular beverage around the world. Its economic value as well as beverage quality are strongly dependent of the quality of beans. The presence of defective beans in coffee blends has caused a negative impact on the beverage Global Quality (GQ) assessed by cupping tests. The main defective beans observed in the productive chain has been those Blacks, Greens and Sours (BGS). Chemical composition of BGS has a damaging impact on beverage GQ. That is why analytical tools are needed for monitoring and controlling the GQ in coffee agro-industry. Near Infrared Spectroscopy (NIRS) has been successfully applied for assessment of coffee quality. Another potential technique for direct, clean and fast measurement of coffee GQ is Laser Induced Breakdown Spectroscopy (LIBS). Elements and diatomic molecules commonly present in organic compounds (structure) can be assessed by using LIBS. In this article is reported an evaluation of LIBS for the main interferents of GQ (BGS defects). Results confirm the great potential of LIBS for discriminating good beans from those with BGS defects by using emission lines of C, CN, C2 and N. Most importantly, some emission lines presented strong linear correlation (r>0.9) with NIRS absorption bands assigned to proteins, lipids, sugar and carboxylic acids, suggesting LIBS potential to estimate these compounds in unroasted and ground coffee samples.

Identification of biochemical features of defective Coffea arabica L. beans

Coffee organoleptic properties are based in part on the quality and chemical composition of coffee beans. The presence of defective beans during processing and roasting contribute to off flavors and reduce overall cup quality. A multipronged approach was undertaken to identify specific biochemical markers for defective beans. To this end, beans were split into defective and non-defective fractions and biochemically profiled in both green and roasted states. A set of 17 compounds in green beans, including organic acids, amino acids and reducing sugars; and 35 compounds in roasted beans, dominated by volatile compounds, organic acids, sugars and sugar alcohols, were sufficient to separate the defective and non-defective fractions. Unsorted coffee was examined for the presence of the biochemical markers to test their utility in detecting defective beans. Although the green coffee marker compounds were found in all fractions, three of the roasted coffee marker compounds (1-methylpyrrole, 5-methyl- 2-furfurylfuran, and 2-methylfuran) were uniquely present in defective fractions.

Qualitative properties of roasting defect beans and development of its classification methods by hyperspectral imaging technology.

Qualitative properties of roasting defect coffee beans and their classification methods were studied using hyperspectral imaging (HSI). The roasting defect beans were divided into 5 groups: medium roasting (Cont), under developed (RD-1), over roasting (RD-2), interior under developed (RD-3), and interior scorching (RD-4). The following qualitative properties were assayed: browning index (BI), moisture content (MC), chlorogenic acid (CA), trigonelline (TG), and caffeine (CF) content. Their HSI spectra (1000-1700nm) were also analysed to develop the classification methods of roasting defect beans. RD-2 showed the highest BI and the lowest MC, CA, and TG content. The accuracy of classification model of partial least-squares discriminant was 86.2%. The most powerful wavelength to classify the defective beans was approximately 1420nm (related to OH bond). The HSI reflectance values at 1420nm showed similar tendency with MC, enabling the use of this technology to classify the roasting defect beans.

The green generation of sunscreens: Using coffee industrial sub-products

Spent coffee grounds and green coffee defective beans, which are industrial sub-products of coffee processing, have a potential use for cosmetic applications, due to their safety and high content in lipids that present interesting physicochemical properties. Sunscreen formulations in the form of water-in-oil emulsions might be a suitable application for these sub-products because providing a higher sun protection factor (SPF) for the same concentration of sunscreen activities than oil-in-water emulsions.The purpose of this work was to assess the biological effects of using the oil fraction of spent coffee grounds extracted with supercritical CO2 and green coffee oil in the development of new generation of sunscreens with improved sun protection performance. The oil fractions were used to prepare w/o sunscreens involving a cold emulsification process, with purified water as disperse aqueous phase and TiO2 and ZnO particles as stabilizers. The sunscreens were characterized in terms of mechanical, rheological and skin adhesion properties. In addition, the in vitro and in vivo biological properties of the formulations were evaluated, including safety and sunscreen water resistance tests.The use of two types of solid particles proved to be useful in the developed formulations, ensuring a high SPF with UVB/A protection, conferred by TiO2 and ZnO, respectively. Moreover, the emulsion containing 35% w/w of the spent coffee grounds oil fraction presented promising characteristics in the improvement of water performance with a broad spectrum sun protection when compared to an emulsion containing 35% w/w of green coffee oil which improved the SPF in physical sunscreens. The formulations are industrial-scalable and suitable for topical use according to the rheological, mechanical and safety assessment.The use of spent coffee oil in cosmetic industry seems to be a suitable approach for the valorisation of waste from the coffee industry and presents promising characteristics in the improvement of sunscreen performance.

Fourier transform infrared spectroscopy and near infrared spectroscopy for the quantification of defects in roasted coffees

The coffee strip-picking harvesting method, preferred in Brazil, results in high percentages of immature and overripe beans, as the fruits in a single tree branch do not reach ripeness at the same time. This practice, together with inappropriate processing and storage conditions, contribute to the production of high amounts of defective coffee beans in Brazil, which upon roasting will impart negative sensory aspects to the beverage. Therefore, the development of analytical methodologies that will enable the discrimination and quantification of defective and non-defective coffees after roasting is rather desirable. Given that infrared spectroscopy has been successfully applied to coffee analysis, the objective of this work was to evaluate and to compare the performances of Fourier transform infrared (FTIR) and near infrared (NIR) spectroscopies for the quantification of defective beans in roasted coffees. Defective and non-defective Arabica coffee beans were manually selected, roasted, ground and sieved. Mixtures of defective and non-defective roasted and ground coffees were produced and analyzed, with % defects ranging from 0% to 30%. FTIR and NIR spectra were recorded, respectively, within a range of 3100–800cm−1 and 1200–2400nm and submitted to mathematical processing. Quantitative models were developed by partial least squares regression (PLSR). Excellent predictive results were obtained indicating that defective coffees could be satisfactorily quantified. The correlation coefficients and the root mean squared errors of validation for the FTIR and NIR models developed to quantify the amount of defective roasted coffees mixed with non-defective ones were, respectively, as high as 0.891 and as low as 0.032, and as high as 0.953 and as low as 0.026. A comparison between the two techniques indicated that NIR provided more robust models.

Discrimination of Defective (Full Black, Full Sour and Immature) and Nondefective Coffee Beans by Their Physical Properties

AbstractIn this research the physical properties of defective and nondefective coffee beans were investigated. The study results show that there are highly significant differences (P &lt; 0.001) in the physical properties (true and bulk volume, true and bulk density, mass) and (P &lt; 0.05) in sphericity and porosity of green coffee beans, respectively. Higher and lower values of mass and dimensional parameters were obtained in full sour and full black coffee beans, respectively. On the other hand, the physical properties of the beans investigated as the function of moisture content (%db) were found to be a linear relation with volume, mass and equivalent diameter, and an inverse relation with density of the beans. Generally, the moisture content (% dry basis [d.b.]) of defective beans (full sour 12.87%, immature 11.34%, full black 10.41%) is higher than nondefective beans (10.22%) for sample kept at oven temperature (105C) for 48 h. The results of the study indicated that the physical properties alone can successfully separate defective and nondefective beans prior and after roasting.Practical ApplicationsThe physical properties of defective and nondefective coffee beans were investigated. The determined physical properties of beans have useful applications in coffee quality control. In addition, these properties have significant importance for machinery and process equipment design. The methods are simple, fast and inexpensive as compared with the chemical methods that need high‐cost equipment and solvents.