Search results for: apple leaf disease recognition
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5883

Search results for: apple leaf disease recognition

5853 Developing a Secure Iris Recognition System by Using Advance Convolutional Neural Network

Authors: Kamyar Fakhr, Roozbeh Salmani

Abstract:

Alphonse Bertillon developed the first biometric security system in the 1800s. Today, many governments and giant companies are considering or have procured biometrically enabled security schemes. Iris is a kaleidoscope of patterns and colors. Each individual holds a set of irises more unique than their thumbprint. Every single day, giant companies like Google and Apple are experimenting with reliable biometric systems. Now, after almost 200 years of improvements, face ID does not work with masks, it gives access to fake 3D images, and there is no global usage of biometric recognition systems as national identity (ID) card. The goal of this paper is to demonstrate the advantages of iris recognition overall biometric recognition systems. It make two extensions: first, we illustrate how a very large amount of internet fraud and cyber abuse is happening due to bugs in face recognition systems and in a very large dataset of 3.4M people; second, we discuss how establishing a secure global network of iris recognition devices connected to authoritative convolutional neural networks could be the safest solution to this dilemma. Another aim of this study is to provide a system that will prevent system infiltration caused by cyber-attacks and will block all wireframes to the data until the main user ceases the procedure.

Keywords: biometric system, convolutional neural network, cyber-attack, secure

Procedia PDF Downloads 189
5852 Generating Synthetic Chest X-ray Images for Improved COVID-19 Detection Using Generative Adversarial Networks

Authors: Muneeb Ullah, Daishihan, Xiadong Young

Abstract:

Deep learning plays a crucial role in identifying COVID-19 and preventing its spread. To improve the accuracy of COVID-19 diagnoses, it is important to have access to a sufficient number of training images of CXRs (chest X-rays) depicting the disease. However, there is currently a shortage of such images. To address this issue, this paper introduces COVID-19 GAN, a model that uses generative adversarial networks (GANs) to generate realistic CXR images of COVID-19, which can be used to train identification models. Initially, a generator model is created that uses digressive channels to generate images of CXR scans for COVID-19. To differentiate between real and fake disease images, an efficient discriminator is developed by combining the dense connectivity strategy and instance normalization. This approach makes use of their feature extraction capabilities on CXR hazy areas. Lastly, the deep regret gradient penalty technique is utilized to ensure stable training of the model. With the use of 4,062 grape leaf disease images, the Leaf GAN model successfully produces 8,124 COVID-19 CXR images. The COVID-19 GAN model produces COVID-19 CXR images that outperform DCGAN and WGAN in terms of the Fréchet inception distance. Experimental findings suggest that the COVID-19 GAN-generated CXR images possess noticeable haziness, offering a promising approach to address the limited training data available for COVID-19 model training. When the dataset was expanded, CNN-based classification models outperformed other models, yielding higher accuracy rates than those of the initial dataset and other augmentation techniques. Among these models, ImagNet exhibited the best recognition accuracy of 99.70% on the testing set. These findings suggest that the proposed augmentation method is a solution to address overfitting issues in disease identification and can enhance identification accuracy effectively.

Keywords: classification, deep learning, medical images, CXR, GAN.

Procedia PDF Downloads 52
5851 Using Speech Emotion Recognition as a Longitudinal Biomarker for Alzheimer’s Diseases

Authors: Yishu Gong, Liangliang Yang, Jianyu Zhang, Zhengyu Chen, Sihong He, Xusheng Zhang, Wei Zhang

Abstract:

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects millions of people worldwide and is characterized by cognitive decline and behavioral changes. People living with Alzheimer’s disease often find it hard to complete routine tasks. However, there are limited objective assessments that aim to quantify the difficulty of certain tasks for AD patients compared to non-AD people. In this study, we propose to use speech emotion recognition (SER), especially the frustration level, as a potential biomarker for quantifying the difficulty patients experience when describing a picture. We build an SER model using data from the IEMOCAP dataset and apply the model to the DementiaBank data to detect the AD/non-AD group difference and perform longitudinal analysis to track the AD disease progression. Our results show that the frustration level detected from the SER model can possibly be used as a cost-effective tool for objective tracking of AD progression in addition to the Mini-Mental State Examination (MMSE) score.

Keywords: Alzheimer’s disease, speech emotion recognition, longitudinal biomarker, machine learning

Procedia PDF Downloads 79
5850 Development of an NIR Sorting Machine, an Experimental Study in Detecting Internal Disorder and Quality of Apple Fruitpple Fruit

Authors: Eid Alharbi, Yaser Miaji

Abstract:

The quality level for fresh fruits is very important for the fruit industries. In presents study, an automatic online sorting system according to the internal disorder for fresh apple fruit has developed by using near infrared (NIR) spectroscopic technology. The automatic conveyer belts system along with sorting mechanism was constructed. To check the internal quality of the apple fruit, apple was exposed to the NIR radiations in the range 650-1300nm and the data were collected in form of absorption spectra. The collected data were compared to the reference (data of known sample) analyzed and an electronic signal was pass to the sorting system. The sorting system was separate the apple fruit samples according to electronic signal passed to the system. It is found that absorption of NIR radiation in the range 930-950nm was higher in the internally defected samples as compared to healthy samples. On the base of this high absorption of NIR radiation in 930-950nm region the online sorting system was constructed.

Keywords: mechatronics, NIR, fruit quality, spectroscopic technology, mechatronic design

Procedia PDF Downloads 368
5849 The Influence of Apple Pomace on Colour and Chemical Composition of Extruded Corn Snack Product

Authors: Jovana Petrovic, Biljana Pajin, Ivana Loncarevic, Aleksandar Fistes, Antun Jozinivic, Durdica Ackar, Drago Subaric

Abstract:

Recovery of food wastes and their conversion to economically viable products will play a vital role for the management strategies in the years to come. Apple pomace may be considered as wastes, but they contain considerable amounts of high value reusable materials. Apple pomace, the by-product of apple juice and cider production, is a good source of fibre, particularly insoluble one. The remaining apple pulp contains 12% dry residue, which is half dietary fibre. Another remarkable aspect is its richness in polyphenols, components with antioxidant activity. Apple pomace could be an interesting alternative source for fibre and polyphenols in extruded corn meals. The extruded corn meals with the addition of finely ground apple pomace were prepared (the ratio of corn meal: apple pomace was 85:15 and 70:30). Characterization of the extrudates in terms of determining the chemical composition and colour was performed. The color of samples was measured by MINOLTA Chroma Meter CR-400 (Minolta Co., Ltd., Osaka, Japan) using D 65 lighting, a 2º standard observer angle and an 8-mm aperture in the measuring head. The following CIELab color coordinates were determined: L* – lightness, a* – redness to greenness and b* – yellowness to blueness. Protein content decreased significantly from 7.91% to 5.19% with increase in pomace from 0% to 30%, while total fibre content increase from 3.39% to 16.62%. The apple pomace addition produced extrudates with a significantly lower L* value and significantly higher a* value. This study has been fully supported by the Provincial Secretariat for High Education and Scientific Research of the Government of Autonomous Province of Vojvodina, Republic of Serbia, project 142-451-2483/2017 and the Ministry of Science and Technological Development of the Republic of Serbia (Project no. 31014).

Keywords: apple pomace, chemical composition, colour, extruded corn snack products, food waste recovery

Procedia PDF Downloads 199
5848 Study of Dormancy-Breaking of Bitter Apple Seed (Citrullus Colocynthis L. Schard)

Authors: Asghar Rahimi, Majid Puryousef

Abstract:

This study aimed to examine dormancy-breaking of bitter apple (Citrullus colocynthis) seed. Seeds of wild bitter apple collected from the Balochestan zone in east of Iran were subjected to different treatments including temperatures (20 and 30°C) and some dormancy breaking methods on breaking seed dormancy of bitter apple. Only 6 treatments from 12 dormancy breaking treatments were effective in dormancy breaking, therefore only effective treatments were analyzed. In general, germination percentage of cleaved seeds, soaked seeds in hot water (98°c) and soaking in H2SO4 in both temperatures was higher than other treatments and germination percentage of scarified seeds with sandy paper in both temperature was lower than other treatments. Also germination percentage of soaked seeds in hot water (98°c) and naturally cracked seeds in temperature 20°c was higher than 30°c.

Keywords: foliar application, nano chelate, nitrogen, Safflower

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5847 Varietal Screening of Watermelon against Powdery Mildew Disease and Its Management

Authors: Asim Abbasi, Amer Habib, Sajid Hussain, Muhammad Sufyan, Iqra, Hasnain Sajjad

Abstract:

Except for few scattered cases, powdery mildew disease was not a big problem for watermelon in the past but with the outbreaks of its pathotypes, races 1W and 2W, this disease becomes a serious issue all around the globe. The severe outbreak of this disease also increased the rate of fungicide application for its proper management. Twelve varieties of watermelon were screened in Research Area of Department of Plant pathology, University of Agriculture, Faisalabad to check the incidence of powdery mildew disease. Disease inoculum was prepared and applied with the help of foliar spray method. Fungicides and plants extracts were also applied after the disease incidence. Percentage leaf surface area diseased was assessed visually with a modified Horsfall-Barratt scale. The results of the experiment revealed that among all varieties, WT2257 and Zcugma F1 were highly resistant showing less than 5% disease incidence while Anar Kali and Sugar baby were highly susceptible with disease incidence of more than 65%. Among botanicals neem extract gave best results with disease incidence of less than 20%. Besides neem, all other botanicals also gave significant control of powdery mildew disease than the untreated check. In case of fungicides, Gemstar showed least disease incidence i.e. < 10%, however besides control maximum disease incidence was observed in Curzate (> 30%).

Keywords: botanicals, fungicides, pathotypes, powdery mildew

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5846 The Green Synthesis AgNPs from Basil Leaf Extract

Authors: Wanida Wonsawat

Abstract:

Bioreduction of silver nanoparticles (AgNPs) from silver ions (Ag+) using water extract of Thai basil leaf was successfully carried out. The basil leaf extract provided a reducing agent and stabilizing agent for a synthesis of metal nanoparticles. Silver nanoparticles received from cut and uncut basil leaf was compared. The resulting silver nanoparticles are characterized by UV-Vis spectroscopy. The maximum intensities of silver nanoparticle from cut and uncut basil leaf were 410 and 420, respectively. The techniques involved are simple, eco-friendly and rapid.

Keywords: basil leaves, silver nanoparticles, green synthesis, plant extract

Procedia PDF Downloads 549
5845 Is there Anything Useful in That? High Value Product Extraction from Artemisia annua L. in the Spent Leaf and Waste Streams

Authors: Anike Akinrinlade

Abstract:

The world population is estimated to grow from 7.1 billion to 9.22 billion by 2075, increasing therefore by 23% from the current global population. Much of the demographic changes up to 2075 will take place in the less developed regions. There are currently 54 countries which fall under the bracket of being defined as having ‘low-middle income’ economies and need new ways to generate valuable products from current resources that is available. Artemisia annua L is well used for the extraction of the phytochemical artemisinin, which accounts for around 0.01 to 1.4 % dry weight of the plant. Artemisinin is used in the treatment of malaria, a disease rampart in sub-Saharan Africa and in many other countries. Once artemisinin has been extracted the spent leaf and waste streams are disposed of as waste. A feasibility study was carried out looking at increasing the biomass value of A. annua, by designing a biorefinery where spent leaf and waste streams are utilized for high product generation. Quercetin, ferulic acid, dihydroartemisinic acid, artemisinic acid and artemsinin were screened for in the waste stream samples and the spent leaf. The analytical results showed that artemisinin, artemisinic acid and dihydroartemisinic acid were present in the waste extracts as well as camphor and arteannuin b. Ongoing effects are looking at using more industrially relevant solvents to extract the phytochemicals from the waste fractions and investigate how microwave pyrolysis of spent leaf can be utilized to generate bio-products.

Keywords: high value product generation, bioinformatics, biomedicine, waste streams, spent leaf

Procedia PDF Downloads 310
5844 The Effect of Aerobic Training and Consumption of Apple Vinegar on Cardiovascular Risk Factor in Older Women

Authors: S. Fazelifar, M. Ghasemi

Abstract:

Aim: Recent studies on cardiovascular risk factors have been focused on the new markers of inflammatory diseases such as C-reactive protein (CRP). Research evidence shows that physical activity along with other factors such as reduced smoking, controlling blood pressure, control blood lipids TC, LDL-c, HDL-c and having a healthy weight can reduce the risk of chronic heart disease (CHD) .Therefore, the aim of this study was to determine the effect of twelve weeks aerobic exercise and consumption of apple vinegar on cardiovascular risk factor in older women. Methodology: 28 inactive women (mean body weight 72.13 ± 8.6 kg, height 157 ± 7.4cm, age 48.06 ± 5.18 years and BMI 28.2 ± 3.2 kg/m2) by recall and notice of investigation, among of the eligible voters recruited and randomly divided in 4 groups: control, apple vinegar, exercise, exercise + apple vinegar. The training program includes a 20-minute warm-up and stretching, running for 15 minutes in the first session with an intensity of 80% of maximum heart rate and an increase in one-minute run time in next training session. Also, subjects in experimental groups received daily specified amount of 50 ml apple vinegar. Blood samples were collected from the brachial vein in before and after training to measure CRP and blood lipids (cholesterol, HDL, VLDL, LDL). The levels of CRP were measured by ELISA way. K-S test to determine the normality of the data and analysis of variance for repeated measures was used to analyze the data. A significant difference in the p < 0/05 accepted. Results: The results indicated that individual characteristics including height, weight, age, and body mass index were not significantly different among the four groups. The results showed that levels of CRP and LDL cholesterol were significantly reduced in all groups at post-test compared to the pre-test. The HDL levels increased significantly in all groups in post-test compared to the pre-test. Analysis of the data indicates that levels of CRP, TC, and LDL were significantly reduced in all groups compared to the control group, while the changes in the other groups were not significant relative to each other. Conclusion: Results of this study showed that twelve weeks of aerobic exercise with apple vinegar cause a significant decrease in CRP, cholesterol, LDL, and significantly increased HDL levels. According to the results of this study, it is possible that aerobic exercise with apple vinegar can inhibit CRP and undesirable fats. Considering the strong association between the inflammatory indices and the prevalence of cardiovascular diseases, every factor that decreases these indices can reduce the cardiovascular complications.

Keywords: aerobic exercise, apple vinegar, CRP, older women

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5843 Experimental Study on Drying Parameters of Freeze Drying Systems

Authors: Ali Osman Suiçmez, Emrah Deniz

Abstract:

In this study, control experiments were made on a freeze drying system of which were built a prototype. In experiments, apple slices in different geometrical shapes were dried and drying curves were gained. Then, the shapes which were the fastest for drying were determined. Twenty samples for each apple shapes were put in the prototype and dried. After the experiments, the humidity ratio of the samples and water activity values of the samples have been obtained. Obtained results show that the prototype is working and by comparing the results the shape which dried fastest was determined.

Keywords: freeze drying, vacuum, energy consumption, drying process, apple

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5842 Effects of Marinating with Cashew Apple Extract on the Bacterial Growth of Beef and Chicken Meat

Authors: S. Susanti, V. P. Bintoro, A. Setiadi, S. I. Santoso, D. R. Febriandi

Abstract:

Meat is a foodstuff of animal origin. It is perishable because a suitable medium for bacterial growth. That is why meat can be a potential hazard to humans. Several ways have been done to inhibit bacterial population in an effort to prolong the meat shelf-life. However, aberration sometimes happens in the practices of meat preservation, for example by using chemical material that possessed strong antibacterial activity like formaldehyde. For health reason, utilization of formaldehyde as a food preservative was forbidden because of DNA damage resulting cancer and birth defects. Therefore, it is important to seek a natural food preservative that is not harmful to the body. This study aims to reveal the potency of cashew apple as natural food preservative by measuring its antibacterial activity and marinating effect on the bacterial growth of beef and chicken meat. Antibacterial activity was measured by The Kirby-Bauer method while bacterial growth was determined by total plate count method. The results showed that inhibition zone of 10-30% cashew apple extract significantly wider compared to 0% extract on the medium of E. coli, S. aureus, S. typii, and Bacillus sp. Furthermore, beef marinated with 20-30% cashew apple extract and chicken meat marinated with 5-15% extract significantly less in the total number of bacteria compared to 0% extract. It can be concluded that marinating with 5-30% cashew apple extract can effectively inhibit the bacterial growth of beef and chicken meat. Moreover, the concentration of extracts to inhibit bacterial populations in chicken meat was reached at the lower level compared to beef. Thus, cashew apple is potential as a natural food preservative.

Keywords: bacterial growth, cashew apple, marinating, meat

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5841 Assessing Digestive Enzymes Inhibitory Properties of Anthocyanins and Procyanidins from Apple, Red Grape, Cinnamon

Authors: Pinar Ercan, Sedef N. El

Abstract:

The goals of this study were to determine the total anthocyanin and procyanidin contents and their in vitro bioaccessibilities of apple, red grape and cinnamon by a static in vitro digestion method reported by the COST FA1005 Action INFOGEST, as well as in vitro inhibitory effects of these food samples on starch and lipid digestive enzymes. While the highest total anthocyanin content was found in red grape (164.76 ± 2.51 mg/100 g), the highest procyanidin content was found in cinnamon (6432.54±177.31 mg/100 g) among the selected food samples (p<0.05). The anthocyanin bioaccessibilities were found as 10.23±1 %, 8.23±0.64 %, and 8.73±0.70 % in apple, red grape, and cinnamon, respectively. The procyanidin bioaccessibilities of apple, red grape, and cinnamon were found as 17.57±0.71 %, 14.08±0.74 % and 18.75±1.49 %, respectively. The analyzed apple, red grape and cinnamon showed the inhibitory activity against α-glucosidase (IC50 544.27±21.94, 445.63±15.67, 1592±17.58 μg/mL, respectively), α-amylase (IC50 38.41±7.26, 56.12±3.60, 3.54±0.86 μg/mL, respectively), and lipase (IC50 52.65±2.05, 581.70±54.14, 49.63±2.72 μg/mL, respectively). Red grape sample showed the highest inhibitory activity against α-glucosidase, cinnamon showed the highest inhibitory activity against α-amylase and lipase according to IC50 (concentration of inhibitor required to produce a 50% inhibition of the initial rate of reaction) and Catechin equivalent inhibition capacity (CEIC50) values. This study reported that apple, grape and cinnamon samples can inhibit the activity of digestive enzymes in vitro. The consumption of these samples would be used in conjunction with a low-calorie diet for body weight management.

Keywords: anthocyanin, α-amylase, α-glucosidase, lipase, procyanidin

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5840 Beneficiation of Dye Sensitized Solar Cell as Energy Saving from Apple Skin with TiO2 Electrolysis

Authors: Astari Indarsari, Bastian B. Purba, Muhammad Fadlilah

Abstract:

In Indonesian climates that have the tropic climate, one of the potential energy sources is coming from solar energy. From the solar energy, we can convert it into the others energy, such as electrical energy. In this topic, we want to do the research about Dye Sensitized Solar Cell (DSSC). The materials that we use as sensitizer is anthocyanin that we extract from apple skin, because the anthocyanin is one of the most effective as a sensitizer for DSSC. The variable in this research is pH. The pH that we used are pH 0,5; pH 1; pH 1,5; pH 2; pH 2,5. The method is electrolysis, and we use TiO2 as sensitized material. The hypothesis from this research is the smaller pH can make higher the efficiency of the absorbent of the solar energy.

Keywords: anthocyanin, TiO2, DSSC, apple skin

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5839 Interactions between Water-Stress and VA Mycorrhizal Inoculation on Plant Growth and Leaf-Water Potential in Tomato

Authors: Parisa Alizadeh Oskuie, Shahram Baghban Ciruse

Abstract:

The influence of arbuscular mycorrhizal (AM) fungus(Glomus mossea) on plant growth and leaf-water potential of tomato (lycopersicum esculentum L.cv.super star) were studied in potted culture water stress stress period of 3 months in greenhouse conditions with the soil matric potential maintained at Fc1, Fc2, Fc3, and Fc4 respectively (0.8,0.7,0.6,0.5 Fc). Seven-day-old seedlings of tomato were transferred to pots containing Glomus mossea or non-AMF. AM colonization significantly stimulated shoot dry matter and leaf-water potential but water stress significantly decreased leaf area, shoot dry matter colonization and leaf-water potential.

Keywords: leaf-water potential, plant growth, tomato, VA mycorrhiza, water-stress

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5838 The Impact of Foliar Application of the Calcium-Containing Compounds in Increasing Resistance to Blue Mold on Apples

Authors: Masoud Baghalian, Musa Arshad

Abstract:

In order to investigate the effect of foliar application of calcium chloride on the resistance of fruits such as Red and Golden Lebanese apple varieties to blue mold, a split plot experiment in time and space, based on accidental blocks, with three replications under foliar application were done (Control, one in a thousand, two in thousands) and the results of the variance analysis showed that there is a significant difference between the levels of foliar and variety at 5% level and between time, there is significant difference in interaction of variety × time and three way interaction of foliar×variety×time, at 1% level. The highest resistance to the blue mold disease in foliar application was observed at two in thousands calcium (calcium chloride) level.

Keywords: apple, blue mold, foliar calcium, resistance

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5837 Effect of Time of Planting on Powdery Mildew Development on Cucumber

Authors: H. Parameshwar Naik, Shripad Kulkarni

Abstract:

Powdery mildew is a serious disease among the fungal in high humid areas with varied temperature conditions. In recent days disease becomes very severe due to uncertain weather conditions and unique character of the disease is, it produces white mycelia growth on upper and lower leaf surfaces and in severe conditions it leads to defoliation. Results of the experiment revealed that sowing of crop in the I fortnight (FN) of July recorded the minimum mean disease severity (7.96 %) followed by crop sown in II FN of July (13.19 %) as against the crop sown in II FN of August (41.44 %) and I FN of September (33.78 %) and the I fortnight of October (33.77 %). In the first date of sowing infection started at 45 DAS and progressed till 73 DAS and it was up to 14.66 Percent and in second date of sowing disease progressed up to 22.66 percent and in the third date of sowing, it was up to 59.35 percent. Afterward, the disease started earlier and progressed up to 66.15 percent and in sixth and seventh date of sowing disease progressed up to 43.15 percent and 59.85 percent respectively. Disease progress is very fast after 45 days after sowing and highest disease incidence was noticed at 73 DAS irrespective of dates of sowing. From the results of the present study, it is very clear that disease development will be very high if crop sown in between 1st fortnight of August and the 1st fortnight of September.

Keywords: cucumber, India, Karnataka, powdery mildew

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5836 Performance Comparison of Deep Convolutional Neural Networks for Binary Classification of Fine-Grained Leaf Images

Authors: Kamal KC, Zhendong Yin, Dasen Li, Zhilu Wu

Abstract:

Intra-plant disease classification based on leaf images is a challenging computer vision task due to similarities in texture, color, and shape of leaves with a slight variation of leaf spot; and external environmental changes such as lighting and background noises. Deep convolutional neural network (DCNN) has proven to be an effective tool for binary classification. In this paper, two methods for binary classification of diseased plant leaves using DCNN are presented; model created from scratch and transfer learning. Our main contribution is a thorough evaluation of 4 networks created from scratch and transfer learning of 5 pre-trained models. Training and testing of these models were performed on a plant leaf images dataset belonging to 16 distinct classes, containing a total of 22,265 images from 8 different plants, consisting of a pair of healthy and diseased leaves. We introduce a deep CNN model, Optimized MobileNet. This model with depthwise separable CNN as a building block attained an average test accuracy of 99.77%. We also present a fine-tuning method by introducing the concept of a convolutional block, which is a collection of different deep neural layers. Fine-tuned models proved to be efficient in terms of accuracy and computational cost. Fine-tuned MobileNet achieved an average test accuracy of 99.89% on 8 pairs of [healthy, diseased] leaf ImageSet.

Keywords: deep convolution neural network, depthwise separable convolution, fine-grained classification, MobileNet, plant disease, transfer learning

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5835 Effect of Lime and Leaf Ash on Engineering Properties of Red Mud

Authors: Pawandeep Kaur, Prashant Garg

Abstract:

Red mud is a byproduct of aluminum extraction from Bauxite industry. It is dumped in a pond which not only uses thousands of acres of land but having very high pH, it pollutes the ground water and the soil also. Leaves are yet another big waste especially during autumn when they contribute immensely to the blockage of drains and can easily catch fire, among other risks hence also needs to be utilized effectively. The use of leaf ash and red mud in highway construction as a filling material may be an efficient way to dispose of leaf ash and red mud. In this study, leaf ash and lime were used as admixtures to improve the geotechnical engineering properties of red mud. The red mud was taken from National Aluminum Company Limited, Odisha, and leaf ash was locally collected. The aim of present study is to investigate the effect of lime and leaf ash on compaction characteristics and strength characteristics of red mud. California Bearing Ratio and Unconfined Compression Strength tests were performed on red mud by varying different percentages of lime and leaf ash. Leaf ash was added in proportion 2%,4%,6%,8% and 10% whereas lime was added in proportions of 5% to 15%. Optimized value of lime was decided with respect to maximum CBR (California Bearing Ratio) of red mud mixed with different proportions of lime. An increase of 300% in California Bearing ratio of red mud and an increase of 125% in Unconfined Compression Strength values were observed. It may, therefore, be concluded that red mud may be effectively utilized in the highway industry as a filler material.

Keywords: stabilization, lime, red mud, leaf ash

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5834 HLB Disease Detection in Omani Lime Trees using Hyperspectral Imaging Based Techniques

Authors: Jacintha Menezes, Ramalingam Dharmalingam, Palaiahnakote Shivakumara

Abstract:

In the recent years, Omani acid lime cultivation and production has been affected by Citrus greening or Huanglongbing (HLB) disease. HLB disease is one of the most destructive diseases for citrus, with no remedies or countermeasures to stop the disease. Currently used Polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELISA) HLB detection tests require lengthy and labor-intensive laboratory procedures. Furthermore, the equipment and staff needed to carry out the laboratory procedures are frequently specialized hence making them a less optimal solution for the detection of the disease. The current research uses hyperspectral imaging technology for automatic detection of citrus trees with HLB disease. Omani citrus tree leaf images were captured through portable Specim IQ hyperspectral camera. The research considered healthy, nutrition deficient, and HLB infected leaf samples based on the Polymerase chain reaction (PCR) test. The highresolution image samples were sliced to into sub cubes. The sub cubes were further processed to obtain RGB images with spatial features. Similarly, RGB spectral slices were obtained through a moving window on the wavelength. The resized spectral-Spatial RGB images were given to Convolution Neural Networks for deep features extraction. The current research was able to classify a given sample to the appropriate class with 92.86% accuracy indicating the effectiveness of the proposed techniques. The significant bands with a difference in three types of leaves are found to be 560nm, 678nm, 726 nm and 750nm.

Keywords: huanglongbing (HLB), hyperspectral imaging (HSI), · omani citrus, CNN

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5833 Face Recognition Using Body-Worn Camera: Dataset and Baseline Algorithms

Authors: Ali Almadan, Anoop Krishnan, Ajita Rattani

Abstract:

Facial recognition is a widely adopted technology in surveillance, border control, healthcare, banking services, and lately, in mobile user authentication with Apple introducing “Face ID” moniker with iPhone X. A lot of research has been conducted in the area of face recognition on datasets captured by surveillance cameras, DSLR, and mobile devices. Recently, face recognition technology has also been deployed on body-worn cameras to keep officers safe, enabling situational awareness and providing evidence for trial. However, limited academic research has been conducted on this topic so far, without the availability of any publicly available datasets with a sufficient sample size. This paper aims to advance research in the area of face recognition using body-worn cameras. To this aim, the contribution of this work is two-fold: (1) collection of a dataset consisting of a total of 136,939 facial images of 102 subjects captured using body-worn cameras in in-door and daylight conditions and (2) evaluation of various deep-learning architectures for face identification on the collected dataset. Experimental results suggest a maximum True Positive Rate(TPR) of 99.86% at False Positive Rate(FPR) of 0.000 obtained by SphereFace based deep learning architecture in daylight condition. The collected dataset and the baseline algorithms will promote further research and development. A downloadable link of the dataset and the algorithms is available by contacting the authors.

Keywords: face recognition, body-worn cameras, deep learning, person identification

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5832 Molluscicidal Effects of Ageratum conyzoids and Datura stramonium on Bulinus globosus and Lymnea natalensis

Authors: Olofintoye Lawrence Kayode, Olorunniyi Omojola Felix

Abstract:

Schistosomiasis is a vector-borne water-based disease transmitted by Bulinus globosus, causing haematuria in the urine of man, while fascioliasis is a trematode zoonosis infectious transmitted by Lymnaea natalensis causing liver disease in man and animals. Adult Bulinus globosus and Lymnaea natalensis were used for the experiment. Aqueous leaf extract of Ageratum conyzoides and Datura stramonium were prepared into 25, 50, 75, 100, 200 and 400 ppm concentrations. Ten snails of each species were exposed to different concentrations in triplicates, and dechlorinated water was used as control at 24h, 48h, and 72h exposure. The results revealed that 100 ppm of both plants leaves extracts indicated mortality rates between 76.7% and 100% at 24h, 48h, and 72h for both snail species. (P<0.05). In conclusion, the extract exercised molluscicidal activity to control the snail vector at lethal doses LC₅₀ (66.611- 72.021 ppm), CI = 63.083-77.90ppm and LC₉₀ (92.623-102.350), CI = 87.715 -110.12 ppm.

Keywords: snail, plant leaf, aqueous extract, mortality

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5831 Evaluation of Non-Destructive Application to Detect Pesticide Residue on Leaf Mustard Using Spectroscopic Method

Authors: Nazmi Mat Nawi, Muhamad Najib Mohamad Nor, Che Dini Maryani Ishkandar

Abstract:

This study was conducted to evaluate the capability of spectroscopic methods to detect the presence of pesticide residues on leaf mustard. A total of 105 leaf mustard used were divided into five batches, four batches were treated with four different types of pesticides whereas one batch with no pesticide applied. Spectral data were obtained using visible shortwave near infrared spectrometer (VSWNIRS) which is Ocean Optics HR4000 High-resolution Miniature Fiber Optic Spectrometer. Reflectance value was collected to determine the difference between one pesticide to the other. The obtained spectral data were pre-processed for optimum performance. The effective wavelength of approximate 880 nm, 675-710 nm also 550 and 700 nm indicates the overtones -CH stretching vibration, tannin, also chlorophyll content present in the leaf mustard respectively. This study has successfully demonstrated that the spectroscopic method was able to differentiate between leaf mustard sample with and without pesticide residue.

Keywords: detect, leaf mustard, non-destructive, pesticide residue

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5830 A Different Approach to Smart Phone-Based Wheat Disease Detection System Using Deep Learning for Ethiopia

Authors: Nathenal Thomas Lambamo

Abstract:

Based on the fact that more than 85% of the labor force and 90% of the export earnings are taken by agriculture in Ethiopia and it can be said that it is the backbone of the overall socio-economic activities in the country. Among the cereal crops that the agriculture sector provides for the country, wheat is the third-ranking one preceding teff and maize. In the present day, wheat is in higher demand related to the expansion of industries that use them as the main ingredient for their products. The local supply of wheat for these companies covers only 35 to 40% and the rest 60 to 65% percent is imported on behalf of potential customers that exhaust the country’s foreign currency reserves. The above facts show that the need for this crop in the country is too high and in reverse, the productivity of the crop is very less because of these reasons. Wheat disease is the most devastating disease that contributes a lot to this unbalance in the demand and supply status of the crop. It reduces both the yield and quality of the crop by 27% on average and up to 37% when it is severe. This study aims to detect the most frequent and degrading wheat diseases, Septoria and Leaf rust, using the most efficiently used subset of machine learning technology, deep learning. As a state of the art, a deep learning class classification technique called Convolutional Neural Network (CNN) has been used to detect diseases and has an accuracy of 99.01% is achieved.

Keywords: septoria, leaf rust, deep learning, CNN

Procedia PDF Downloads 46
5829 Oil Palm Leaf and Corn Stalk, Mechanical Properties and Surface Characterization

Authors: Zawawi Daud

Abstract:

Agro waste can be defined as waste from agricultural plant. Oil palm leaf and corn stalk can be categorized as ago waste material. At first, the comparison between oil palm leaf and corn stalk by mechanical properties from soda pulping process. After that, focusing on surface characterization by Scanning Electron Microscopy (SEM). Both material have a potential due to mechanical properties (tensile, tear, burst and fold) and surface characterization but corn stalk shows more in strength and compactness due to fiber characterization compared to oil palm leaf. This study promoting the green technology in develop a friendly product and suitable to be used as an alternative pulp in paper making industry.

Keywords: fiber, oil palm leaf, corn stalk, green technology

Procedia PDF Downloads 457
5828 Handwriting Recognition of Gurmukhi Script: A Survey of Online and Offline Techniques

Authors: Ravneet Kaur

Abstract:

Character recognition is a very interesting area of pattern recognition. From past few decades, an intensive research on character recognition for Roman, Chinese, and Japanese and Indian scripts have been reported. In this paper, a review of Handwritten Character Recognition work on Indian Script Gurmukhi is being highlighted. Most of the published papers were summarized, various methodologies were analysed and their results are reported.

Keywords: Gurmukhi character recognition, online, offline, HCR survey

Procedia PDF Downloads 396
5827 Papaya Leaf in Broiler Chicken Feed Reducing Lipid Peroxidation of Meat

Authors: M. Ebrahimi, E. Maroufyan, M. Shakeri, E. Oskoueian, A. F Soleimani, Y. M. Goh

Abstract:

Lipid peroxidation is a main reason of low quality in meat and meat products. The free radical chain reaction is the major process of lipid peroxidation and reactive oxygen species (ROS) such as hydroxyl radical and hydroperoxyl radical are the main starter of the chain reaction. Papaya leaf contains several secondary metabolites which can be used as a potential antioxidant in broiler feed. Hence, this research was carried out to evaluate the potential of papaya leaf to prevent lipid peroxidation and enhance the antioxidant activity of breast meat of broiler chicken. The results showed that supplementation of papaya leaf at 5%, significantly (p < 0.05) reduced the lipid peroxidation compared to control group. The supplementation of papaya leaf prevented from lipid peroxidation and enhanced the antioxidant activity of the broiler breast meat significantly (p < 0.05) after different storage periods. Papaya leaf reduced the lipid oxidation of meat during storage with strong free radical-scavenging ability. In conclusion, supplementation of papaya leaf in broiler diet to have high quality meat is recommended.

Keywords: antioxidant activity, papaya leaf, breast meat, lipid peroxidation

Procedia PDF Downloads 569
5826 OCR/ICR Text Recognition Using ABBYY FineReader as an Example Text

Authors: A. R. Bagirzade, A. Sh. Najafova, S. M. Yessirkepova, E. S. Albert

Abstract:

This article describes a text recognition method based on Optical Character Recognition (OCR). The features of the OCR method were examined using the ABBYY FineReader program. It describes automatic text recognition in images. OCR is necessary because optical input devices can only transmit raster graphics as a result. Text recognition describes the task of recognizing letters shown as such, to identify and assign them an assigned numerical value in accordance with the usual text encoding (ASCII, Unicode). The peculiarity of this study conducted by the authors using the example of the ABBYY FineReader, was confirmed and shown in practice, the improvement of digital text recognition platforms developed by Electronic Publication.

Keywords: ABBYY FineReader system, algorithm symbol recognition, OCR/ICR techniques, recognition technologies

Procedia PDF Downloads 135
5825 The Use of Food Industry Bio-Products for Sustainable Lactic Acid Bacteria Encapsulation

Authors: Paulina Zavistanaviciute, Vita Krungleviciute, Elena Bartkiene

Abstract:

Lactic acid bacteria (LAB) are microbial supplements that increase the nutritional, therapeutic, and safety value of food and feed. Often LAB strains are incubated in an expensive commercially available de Man-Rogosa-Sharpe (MRS) medium; the cultures are centrifuged, and the cells are washing with sterile water. Potato juice and apple juice industry bio-products are industrial wastes which may constitute a source of digestible nutrients for microorganisms. Due to their low cost and good chemical composition, potato juice and apple juice production bio- products could have a potential application in LAB encapsulation. In this study, pure LAB (P. acidilactici and P. pentosaceus) were multiplied in a crushed potato juice and apple juice industry bio-products medium. Before using, bio-products were sterilized and filtered. No additives were added to mass, except apple juice industry bioproducts were diluted with sterile water (1/5; v/v). The tap of sterilised mass, and LAB cell suspension (5 mL), containing of 8.9 log10 colony-forming units (cfu) per mL of the P. acidilactici and P. pentosaceus was used to multiply the LAB for 72 h. The final colony number in the potato juice and apple juice bio- products substrate was on average 9.60 log10 cfu/g. In order to stabilize the LAB, several methods of dehydration have been tested: lyophilisation (MilrockKieffer Lane, Kingston, USA) and dehydration in spray drying system (SD-06, Keison, Great Britain). Into the spray drying system multiplied LAB in a crushed potato juice and apple juice bio-products medium was injected in peristaltic way (inlet temperature +60 °C, inlet air temperature +150° C, outgoing air temperature +80 °C, air flow 200 m3/h). After lyophilisation (-48 °C) and spray drying (+150 °C) the viable cell concentration in the fermented potato juice powder was 9.18 ± 0.09 log10 cfu/g and 9.04 ± 0.07 log10 cfu/g, respectively, and in apple mass powder 8.03 ± 0.04 log10 cfu/g and 7.03 ± 0.03 log10 cfu/g, respectively. Results indicated that during the storage (after 12 months) at room temperature (22 +/- 2 ºC) LAB count in dehydrated products was 5.18 log10 cfu/g and 7.00 log10 cfu/g (in spray dried and lyophilized potato juice powder, respectively), and 3.05 log10 cfu/g and 4.10 log10 cfu/g (in spray dried and lyophilized apple juice industry bio-products powder, respectively). According to obtained results, potato juice could be used as alternative substrate for P. acidilactici and P. pentosaceus cultivation, and by drying received powders can be used in food/feed industry as the LAB starters. Therefore, apple juice industry by- products before spray drying and lyophilisation should be modified (i. e. by using different starches) in order to improve its encapsulation.

Keywords: bio-products, encapsulation, lactic acid bacteria, sustainability

Procedia PDF Downloads 251
5824 The Effect of Brassica rapa Leaf Extracts on the Growth of Upland Ipomoea aquatica

Authors: Keziah Bazar

Abstract:

The effect of Brassica rapa leaf extracts on the growth of upland Ipomoea aquatica was investigated. One hundred grams Brassica rapa leaf were blended using a heavy duty blender. These were diluted with water to have final concentrations of 75% (T1), 50% (T2) and 25% (T3) that served as treatments of the study. Pure water (T0) that served as control was also included Upland Ipomoea aquatic were grown in pots. A 3-4 in water level was maintained during the whole duration of the study. Plant height, leaf area, fruit size and shoot height, were taken after 6 months. Results showed that plant height and shoot height was highest in T1 while T0 was the lowest. On the other hand, T2 had the highest leaf area and fruit size. The study suggests that T1 and T2 can be a good fertilizer for Ipomoea aquatica.

Keywords: Ipomoea aquatica, leaf extracts, growth, Brassica rapa

Procedia PDF Downloads 186