Abstract: The aim of this study is to develop a system which can identify and sort peaberries automatically at low cost for coffee producers in developing countries. In this paper, the focus is on the classification of peaberries and normal coffee beans using image processing and machine learning techniques. The peaberry is not bad and not a normal bean. The peaberry is born in an only single seed, relatively round seed from a coffee cherry instead of the usual flat-sided pair of beans. It has another value and flavor. To make the taste of the coffee better, it is necessary to separate the peaberry and normal bean before green coffee beans roasting. Otherwise, the taste of total beans will be mixed, and it will be bad. In roaster procedure time, all the beans shape, size, and weight must be unique; otherwise, the larger bean will take more time for roasting inside. The peaberry has a different size and different shape even though they have the same weight as normal beans. The peaberry roasts slower than other normal beans. Therefore, neither technique provides a good option to select the peaberries. Defect beans, e.g., sour, broken, black, and fade bean, are easy to check and pick up manually by hand. On the other hand, the peaberry pick up is very difficult even for trained specialists because the shape and color of the peaberry are similar to normal beans. In this study, we use image processing and machine learning techniques to discriminate the normal and peaberry bean as a part of the sorting system. As the first step, we applied Deep Convolutional Neural Networks (CNN) and Support Vector Machine (SVM) as machine learning techniques to discriminate the peaberry and normal bean. As a result, better performance was obtained with CNN than with SVM for the discrimination of the peaberry. The trained artificial neural network with high performance CPU and GPU in this work will be simply installed into the inexpensive and low in calculation Raspberry Pi system. We assume that this system will be used in under developed countries. The study evaluates and compares the feasibility of the methods in terms of accuracy of classification and processing speed.
Abstract: The development of value added composite products from bamboo with the application of gluing technology can play a vital role in economic development and also in forest resource conservation of any country. In this study, the gluability of Bambusa balcooa and Bambusa vulgaris, two locally grown bamboo species of Bangladesh was assessed. As the culm wall thickness of bamboos decreases from bottom to top, a culm portion of up to 5.4 m and 3.6 m were used from the base of B. balcooa and B. vulgaris, respectively, to get rectangular strips of uniform thickness. The color of the B. vulgaris strips was yellowish brown and that of B. balcooa was reddish brown. The strips were treated in borax-boric, bleaching and carbonization for extending the service life of the laminates. The preservative treatments changed the color of the strips. Borax–boric acid treated strips were reddish brown. When bleached with hydrogen peroxide, the color of the strips turned into whitish yellow. Carbonization produced dark brownish strips having coffee flavor. Chemical constituents for untreated and treated strips were determined. B. vulgaris was more acidic than B. balcooa. Then the treated strips were used to develop three-layered bamboo laminated panel. Urea formaldehyde (UF) and polyvinyl acetate (PVA) were used as binder. The shear strength and abrasive resistance of the panel were evaluated. It was found that the shear strength of the UF-panel was higher than the PVA-panel for all treatments. Between the species, gluability of B. vulgaris was better and in some cases better than hardwood species. The abrasive resistance of B. balcooa is slightly higher than B. vulgaris; however, the latter was preferred as it showed well gluability. The panels could be used as structural panel, floor tiles, flat pack furniture component, and wall panel etc. However, further research on durability and creep behavior of the product in service condition is warranted.
Abstract: Consumers are demanding novel beverages that are
healthier, convenient and have appealing consumer acceptance. The
objectives of this study were to investigate the effects of adding grape
polyphenols and the influence of presenting health claims on the
sensory acceptability of wines. Fresh red sorrel calyces were
fermented into wines. The total soluble solids of the pectinase-treated
sorrel puree were from 4°Brix to 23.8°Brix. Polyphenol in the form
of grape pomace extract was added to sorrel wines (w/v) in specified
levels to give 0. 25. 50 and 75 ppm. A focus group comprising of 12
panelists was use to select the level of polyphenol to be added to
sorrel wines for sensory preference The sensory attributed of the
wines which were evaluated were colour, clarity, aroma, flavor,
mouth-feel, sweetness, astringency and overall preference. The sorrel
wine which was most preferred from focus group evaluation was
presented for hedonic rating. In the first stage of hedonic testing, the
sorrel wine was served chilled at 7°C for 24 h prior to sensory
evaluation. Each panelist was provided with a questionnaire and was
asked to rate the wines on colour, aroma, flavor, mouth-feel,
sweetness, astringency and overall acceptability using a 9-point
hedonic scale. In the second stage of hedonic testing, the panelist
were instructed to read a health abstract on the health benefits of
polyphenolic compounds and again to rate sorrel wine with added 25
ppm polyphenol. Paired t-test was used for the analysis of the
influence of presenting health information on polyphenols on hedonic
scoring of sorrel wines. Focus groups found that the addition of
polyphenol addition had no significant effect on sensory color and
aroma but affected clarity and flavor. A 25 ppm wine was liked
moderately in overall acceptability. The presentation of information
on the health benefit of polyphenols in sorrel wines to panelists had
no significant influence on the sensory acceptance of wine. More
than half of panelists would drink this wine now and then. This wine
had color L 19.86±0.68, chroma 2.10±0.12, hue° 16.90 ±3.10 and
alcohol content of 13.0%. The sorrel wine was liked moderately in
overall acceptability with the added polyphenols.
Abstract: The research of juice flavor forecasting has become
more important in China. Due to the fast economic growth in China,
many different kinds of juices have been introduced to the market. If a
beverage company can understand their customers’ preference well,
the juice can be served more attractive. Thus, this study intends to
introducing the basic theory and computing process of grapes juice
flavor forecasting based on support vector regression (SVR). Applying
SVR, BPN, and LR to forecast the flavor of grapes juice in real data
shows that SVR is more suitable and effective at predicting
performance.
Abstract: Aroma forming volatiles are important components of
fermented beverages. The aim of current research is to evaluate the
volatile compounds and phenolic compounds of commercial ciders.
Volatile aroma compounds and TPC of seven commercial ciders
were determined. Extraction of aroma compounds was performed
using solid phase microextraction (DVB/Car/PDMS fibre). Analysis
of volatile aroma compounds was made using a Perkin Elmer Clarus
500 GC/MS. Total phenol content (TPC) was determined according
to the Folin-Ciocalteu spectrophotometric method and results were
expressed as gallic acid equivalents. The highest volatile compounds
were in apple ciders with pear flavor. The highest TPC and lower
content of volatile compounds were detected in French ciders.
Abstract: The changes in quality properties and nutritional
components in two fermented mugworts (Artemisia capillaries
Thumberg, Artemisiaeasiaticae Nakai) were characterized followed
by the rapid pattern analysis of volatile flavor compounds by Electric
Nose based on SAW(Surface Acoustic Wave) sensor in GC system.
There were remarkable decreases in the pH and small changes in the
total soluble solids after fermentation. The L (lightness) and b
(yellowness) values in Hunter's color system were shown to be
decreased, whilst the a (redness) value was increased by fermentation.
The HPLC analysis demonstrated that total amino acids were
increased in quantity and the essential amino acids were contained
higher in A. asiaticaeNakai than in A. capillaries Thumberg. While
the total polyphenol contents were not affected by fermentation, the
total sugar contents were dramatically decreased. Scopoletinwere
highly abundant in A. capillarisThumberg, however, it was not
detected in A. asiaticaeNakai. Volatile flavor compounds by Electric
Nose showed that the intensity of several peaks were increased much
and seven additional flavor peaks were newly produced after
fermentation. The flavor differences of two mugworts were clearly
distinguished from the image patterns of VaporPrintTM which indicate
that the fermentation enables the two mugworts to have subtle flavor
differences.