Search results for: artificial food

Authors: Lynette Lincoln, Sunil S. More

Abstract:

With the rising demand of sugar used today, it is proposed that world sugar is expected to escalate up to 203 million tonnes by 2021. Hydrolysis of sucrose (table sugar) into glucose and fructose equimolar mixture is catalyzed by β-D-fructofuranoside fructohydrolase (EC 3.2.1.26), commonly called as invertase. For fluid filled center in chocolates, preparation of artificial honey, as a sweetener and especially to ensure that food stuffs remain fresh, moist and soft for longer spans invertase is applied widely and is extensively being used. From an industrial perspective, properties such as increased solubility, osmotic pressure and prevention of crystallization of sugar in food products are highly desired. Screening for invertase does not involve plate assay/qualitative test to determine the enzyme production. In this study, we use a three-step screening strategy for identification of a novel bacterial isolate from soil which is positive for invertase production. The primary step was serial dilution of soil collected from sugarcane fields (black soil, Maddur region of Mandya district, Karnataka, India) was grown on a Czapek-Dox medium (pH 5.0) containing sucrose as the sole C-source. Only colonies with the capability to utilize/breakdown sucrose exhibited growth. Bacterial isolates released invertase in order to take up sucrose, splitting the disaccharide into simple sugars. Secondly, invertase activity was determined from cell free extract by measuring the glucose released in the medium at 540 nm. Morphological observation of the most potent bacteria was examined by several identification tests using Bergey’s manual, which enabled us to know the genus of the isolate to be Bacillus. Furthermore, this potent bacterial colony was subjected to 16S rDNA PCR amplification and a single discrete PCR amplicon band of 1500 bp was observed. The 16S rDNA sequence was used to carry out BLAST alignment search tool of NCBI Genbank database to obtain maximum identity score of sequence. Molecular sequencing and identification was performed by Xcelris Labs Ltd. (Ahmedabad, India). The colony was identified as Bacillus sp. BAB-3434, indicating to be the first novel strain for extracellular invertase production. Molasses, a by-product of the sugarcane industry is a dark viscous liquid obtained upon crystallization of sugar. An enhanced invertase production and optimization studies were carried out by one-factor-at-a-time approach. Crucial parameters such as time course (24 h), pH (6.0), temperature (45 °C), inoculum size (2% v/v), N-source (yeast extract, 0.2% w/v) and C-source (molasses, 4% v/v) were found to be optimum demonstrating an increased yield. The findings of this study reveal a simple screening method of an extracellular invertase from a rapidly growing Bacillus sp., and selection of best factors that elevate enzyme activity especially utilization of molasses which served as an ideal substrate and also as C-source, results in a cost-effective production under submerged conditions. The invert mixture could be a replacement for table sugar which is an economic advantage and reduce the tedious work of sugar growers. On-going studies involve purification of extracellular invertase and determination of transfructosylating activity as at high concentration of sucrose, invertase produces fructooligosaccharides (FOS) which possesses probiotic properties.

Keywords: Bacillus sp., invertase, molasses, screening, submerged fermentation

Procedia PDF Downloads 231

Authors: Vipul M. Patel, Hemantkumar B. Mehta

Abstract:

Technological innovations in electronic world demand novel, compact, simple in design, less costly and effective heat transfer devices. Closed Loop Pulsating Heat Pipe (CLPHP) is a passive phase change heat transfer device and has potential to transfer heat quickly and efficiently from source to sink. Thermal performance of a CLPHP is governed by various parameters such as number of U-turns, orientations, input heat, working fluids and filling ratio. The present paper is an attempt to predict the thermal performance of a CLPHP using Artificial Neural Network (ANN). Filling ratio and heat input are considered as input parameters while thermal resistance is set as target parameter. Types of neural networks considered in the present paper are radial basis, generalized regression, linear layer, cascade forward back propagation, feed forward back propagation; feed forward distributed time delay, layer recurrent and Elman back propagation. Linear, logistic sigmoid, tangent sigmoid and Radial Basis Gaussian Function are used as transfer functions. Prediction accuracy is measured based on the experimental data reported by the researchers in open literature as a function of Mean Absolute Relative Deviation (MARD). The prediction of a generalized regression ANN model with spread constant of 4.8 is found in agreement with the experimental data for MARD in the range of ±1.81%.

Keywords: ANN models, CLPHP, filling ratio, generalized regression, spread constant

Procedia PDF Downloads 287

Authors: Debabrata Biswas

Abstract:

The current trend in the development of antibiotic resistance by multiple bacterial pathogens has resulted in a troubling loss of effective antibiotic options for human. The emergence of multi-drug-resistant pathogens has necessitated higher dosages and combinations of multiple antibiotics, further exacerbating the problem of antibiotic resistance. Zoonotic bacterial pathogens, such as Salmonella, Campylobacter, Shiga toxin-producing Escherichia coli (such as enterohaemorrhagic E. coli or EHEC), and Listeria are the most common and predominant foodborne enteric infectious agents. It was observed that these pathogens gained/developed their ability to survive in the presence of antibiotics either in farm animal gut or farm environment and researchers believe that therapeutic and sub-therapeutic antibiotic use in farm animal production might play an important role in it. The mechanism of action of antimicrobial components used in farm animal production in genomic interplay in the gut and farm environment, has not been fully characterized. Even the risk of promoting the exchange of mobile genetic elements between microbes specifically pathogens needs to be evaluated in depth, to ensure sustainable farm animal production, safety of our food and to mitigate/limit the enteric infection with multiple antibiotic resistant bacterial pathogens. Due to the consumer’s demand and considering the current emerging situation, many countries are in process to withdraw antibiotic use in farm animal production. Before withdrawing use of the sub-therapeutic antibiotic or restricting the use of therapeutic antibiotics in farm animal production, it is essential to find alternative natural antimicrobials for promoting the growth of farm animal and/or treating animal diseases. Further, it is also necessary to consider whether that compound(s) has the potential to trigger the acquisition or loss of genetic materials in zoonotic and any other bacterial pathogens. Development of alternative therapeutic and sub-therapeutic antimicrobials for farm animal production and food processing and preservation and their effective implementation for sustainable strategies for farm animal production as well as the possible risk for horizontal gene transfer in major enteric pathogens will be focus in the study.

Keywords: food safety, natural antimicrobial, sustainable farming, antibiotic resistance

Procedia PDF Downloads 264

Authors: António Inês, Ana Guimarães, José Maria, Vânia Laranjo, Armando Venâncio, Luís Abrunhosa

Abstract:

Lactic acid bacteria (LAB) play a key role in the biopreservation of a wide range of fermented food products, such as yogurt, cheese, fermented milks, meat, fish, vegetables (sauerkraut, olives and pickles), certain beer brands, wines and silage, allowing their safe consumption, which gave to these bacteria a GRAS (Generally Recognised as Safe) status. Besides that, the use of LAB in food and feed is a promising strategy to reduce the exposure to dietary mycotoxins, improving their shelf life and reducing health risks, given the unique mycotoxin decontaminating characteristic of some LAB. Mycotoxins present carcinogenic, mutagenic, teratogenic, neurotoxic and immunosuppressive effects over animals and Humans, being the most important ochratoxin A (OTA), aflatoxins (AFB1), trichothecenes, zearalenone (ZEA), fumonisin (FUM) and patulin. In a previous work of our group it was observed OTA biodegradation by some strains of Pediococcus parvulus isolated from Douro wines. So, the aim of this study was to enlarge the screening of the biodetoxification over more mycotoxins besides OTA, including AFB1, and ZEA. This ability was checked in a collection of LAB isolated from vegetable (wine, olives, fruits and silage) and animal (milk and dairy products, sausages) sources. All LAB strains were characterized phenotypically (Gram, catalase) and genotypically. Molecular characterisation of all LAB strains was performed using genomic fingerprinting by MSP-PCR with (GTG)5 and csM13 primers. The identification of the isolates was confirmed by 16S rDNA sequencing. To study the ability of LAB strains to degrade OTA, AFB1 and ZEA, a MRS broth medium was supplemented with 2.0 μg/mL of each mycotoxin. For each strain, 2 mL of MRS supplemented with the mycotoxins was inoculated in triplicate with 109 CFU/mL. The culture media and bacterial cells were extracted by the addition of an equal volume of acetonitrile/methanol/acetic acid (78:20:2 v/v/v) to the culture tubes. A 2 mL sample was then collected and filtered into a clean 2 mL vial using PP filters with 0.45 μm pores. The samples were preserved at 4 °C until HPLC analysis. Among LAB tested, 10 strains isolated from milk were able to eliminate AFB1, belonging to Lactobacillus casei (7), Lb. paracasei (1), Lb. plantarum (1) and 1 to Leuconostoc mesenteroides. Two strains of Enterococcus faecium and one of Ec. faecalis from sausage eliminated ZEA. Concerning to strains of vegetal origin, one Lb. plantarum isolated from elderberry fruit, one Lb. buchnerii and one Lb. parafarraginis both isolated from silage eliminated ZEA. Other 2 strains of Lb. plantarum from silage were able to degrade both ZEA and OTA, and 1 Lb. buchnerii showed activity over AFB1. These enzymatic activities were also verified genotypically through specific gene PCR and posteriorly confirmed by sequencing analysis. In conclusion, due the ability of some strains of LAB isolated from different sources to eliminate OTA, AFB1 and ZEA one can recognize their potential biotechnological application to reduce the health hazards associated with these mycotoxins. They may be suitable as silage inoculants or as feed additives or even in food industry.

Keywords: bio-detoxification, lactic acid bacteria, mycotoxins, food and feed

Procedia PDF Downloads 563

Authors: Ramadhani Yasyfi Cysela, Adinda Syifa Azhari, Eleonora Agustine

Abstract:

The World Health Organization (WHO) estimates that about a quarter of the diseases facing mankind today occur due to environmental pollution. The soil is a part of environment that have a widespread problem. The contaminated soil should no longer be used to grow food because the chemicals can leech into the food and harm people who eat it. The chemical fertilizer industry gives specific effect due to soil pollution. To determine ammonia and urea emissions from fertilizer industry, we can use physical characteristic of soil, which is magnetic susceptibility. Rock magnetism is used as a proxy indicator to determine changes in physical properties. Magnetic susceptibilities of samples in low and high frequency have been measured by Bartington MS2B magnetic susceptibility measurement device. The sample was taken from different area which located closer by pollution source and far from the pollution source. The susceptibility values of polluted samples in topsoil were quite low, with range from 187.1- 494.8 [x 10-8 m3 kg-1] when free polluted area’s sample has high values (1188.7- 2237.8 [x 10-8 m3 kg-1 ]). From this studies shows that susceptibility values in areas of the fertilizer industry are lower than the free polluted area.

Keywords: environmental, magnetic susceptibility, rock magnetism, soil pollution

Procedia PDF Downloads 350

Authors: Jackson Ishara, Ariel Buzera, Gustave N. Mushagalusa, Ahmed R. A. Hammam, Judith Munga, Paul Karanja, John Kinyuru

Abstract:

Numerous mushroom bioactive metabolites, including polysaccharides, eritadenine, lignin, chitosan, mevinolin, and astrakurkurone have been studied in life-threatening conditions and diseases such as diabetes, cardiovascular, hypertension, cancer, DNA damage, hypercholesterolemia, and obesity attempting to identify natural therapies. These bioactive metabolites have shown potential as antiviral and immune system strengthener natural agents through diverse cellular and physiological pathways modulation with no toxicity evidence, widely available, and affordable. In light of the emerging literature, this paper compiles the most recent information describing the molecular mechanisms that underlie the nutraceutical potentials of these mushroom metabolites suggesting their effectiveness if combined with existing drug therapies. The findings raise hope that these mushroom bioactive metabolites may be utilized as natural therapies considering their therapeutic potential while anticipating further research designing clinical trials and developing new drug therapies while encouraging their consumption as a natural adjuvant in preventing and controlling life-threatening conditions and diseases.

Keywords: bioactive metabolites, food functionality, health-threatening conditions, mushrooms, nutraceutical

Procedia PDF Downloads 96

Authors: Donna M. Morrison, Lambert Chester, Coretta A. N. Samuels, David R. Ledoux

Abstract:

A survey was conducted in the five rice-growing regions in Guyana to determine the presence of aflatoxins in multiple fractions of rice in June/October 2015 growing season. The fractions were paddy, steamed paddy, cargo rice, white rice and parboiled rice. Samples were analyzed by High Performance Liquid Chromatography. A subset of the samples was further analyzed by enzyme-linked immunosorbent assay (ELISA) for concurrence. All analyses were conducted at the University of Missouri, USA. Of the 186 samples tested, 16 had aflatoxin concentrations greater than 20 ppb the recommended limit for aflatoxins in food according to the United States Food and Drug Administration. An additional three samples had aflatoxin B₁ concentrations greater than the European Union Commission maximum levels for aflatoxin B₁ in rice at 5 µg/kg and total aflatoxins (B₁, B₂, G₁ and G₂) at 10 µg/kg. The survey indicates that there is no widespread aflatoxin problem in rice in Guyana. The incidence of aflatoxins appears to be localized.

Keywords: aflatoxin, enzyme-linked immunosorbent assay (ELISA), high-performance liquid chromatography (HPLC), rice fractions

Procedia PDF Downloads 261

Authors: EMMANUEL DWAMENA SASU

Abstract:

International climate policy actions require countries under Paris Agreement to design instruments, provide support (financial and technical), and strengthen institutional capacity with tendency to transcending policy formulation to implementation and sustainability. Changes associated with moisture depletion has been a growing phenomenon; especially in developing countries with projected global GDP drop from 7% to 2% between 2005 and 2050. These developments have potential to adversely affect food production in feeding the growing world population, with corresponding rise in global hunger. Incongruously, there is global absence of a harmonized policy direction; capable of providing the required indicators on climate policies for monitoring sustainability of international agricultural development projects. We conduct extensive review and synthesis on existing limitations on global climate policy governance, agricultural food security and sustainability of international agricultural development projects, and conjecture the role of non-state and sub-national climate stakeholder engagements, and monitoring and evaluation strategies for improved climate policy action for sustaining international agricultural development projects.

Keywords: climate policy, agriculture, development projects, sustainability

Procedia PDF Downloads 119

Authors: Pontsho E. Tseke, Phatu W. Mashela

Abstract:

Climate-smart agriculture dictates that underusilised indigenous plant, which served as food for local marginalized communities, be assessed for introduction into mainstream agriculture. Most of the underutilised indigenous plants had survived adverse conditions in the wild; with limited information on how the interact with most abiotic and biotic factors. Cucumis myriocarpus leafy vegetable has nutritional, pharmacological and industrial applications, with limited information on how it interacts with effective microorganisms. The objective of this study was to determine the effects vesicular arbuscular mycorrhiza (VAM) on the growth of C. myriocarpus indigenous leafy vegetable under greenhouse conditions. Four-weeks-old seedlings of C. myriocarpus were transplanted into 20-cm-diameter plastic pots. Two weeks after transplanting, VAM was applied at 0, 10, 20, 30, 40, 50, 60 and 70 g Biocult-VAM plant. At 56 days after treatments, plant growth variables of C. myriocarpus with increase Biocult-VAM levels exhibited positive quadratic relations. Plant variables and increasing concentrations of salinity exhibited positive quadric relations, with 95 to 99% associations. Inclusion, Biocult-VAM can be used in sustainable production of C. myriocarpus for functional food security.

Keywords: abiotic, biotic, rhizasphere, sustainable agriculture

Procedia PDF Downloads 272

Authors: C. E. Ogbanje, S. A. N. D. Chidebelu, N. J. Nweze

Abstract:

The study evaluated off-farm work and cost efficiency in staple food production among small-scale farmers in North Central Nigeria. Multistage sampling technique was used to select 360 respondents (participants and non-participants in off-farm work). Primary data obtained were analysed using stochastic cost frontier and test of means’ difference. Capital input was lower for participants (N2,596.58) than non-participants (N11,099.14). Gamma (γ) was statistically significant. Farm size significantly (p<0.01) increased cost outlay for participants and non-participants. Average input prices of enterprises one and two significantly (p<0.01) increased cost. Sex, household size, credit obtained, formal education, farming experience, and farm income significantly (p<0.05) reduced cost inefficiency for non-participants. Average cost efficiency was 11%. Farm capital was wasted. Participants’ substitution of capital for labour did not put them at a disadvantage. Extension agents should encourage farmers to obtain financial relief from off-farm work but not to the extent of endangering farm cost efficiency.

Keywords: cost efficiency, mean difference, North Central Nigeria, off-farm work, participants and non-participants, small-scale farmers

Procedia PDF Downloads 361

Authors: Martins Y. Otache, John J. Musa, Abayomi I. Kuti, Mustapha Mohammed

Abstract:

The performance of an artificial neural network (ANN) is contingent on a host of factors, for instance, the network optimisation scheme. In view of this, the study examined the general implications of the ANN training optimisation algorithm on its forecast performance. To this end, the Bayesian regularisation (Br), Levenberg-Marquardt (LM), and the adaptive learning gradient descent: GDM (with momentum) algorithms were employed under different ANN structural configurations: (1) single-hidden layer, and (2) double-hidden layer feedforward back propagation network. Results obtained revealed generally that the gradient descent with momentum (GDM) optimisation algorithm, with its adaptive learning capability, used a relatively shorter time in both training and validation phases as compared to the Levenberg- Marquardt (LM) and Bayesian Regularisation (Br) algorithms though learning may not be consummated; i.e., in all instances considering also the prediction of extreme flow conditions for 1-day and 5-day ahead, respectively especially using the ANN model. In specific statistical terms on the average, model performance efficiency using the coefficient of efficiency (CE) statistic were Br: 98%, 94%; LM: 98 %, 95 %, and GDM: 96 %, 96% respectively for training and validation phases. However, on the basis of relative error distribution statistics (MAE, MAPE, and MSRE), GDM performed better than the others overall. Based on the findings, it is imperative to state that the adoption of ANN for real-time forecasting should employ training algorithms that do not have computational overhead like the case of LM that requires the computation of the Hessian matrix, protracted time, and sensitivity to initial conditions; to this end, Br and other forms of the gradient descent with momentum should be adopted considering overall time expenditure and quality of the forecast as well as mitigation of network overfitting. On the whole, it is recommended that evaluation should consider implications of (i) data quality and quantity and (ii) transfer functions on the overall network forecast performance.

Keywords: streamflow, neural network, optimisation, algorithm

Procedia PDF Downloads 150

Authors: Vanja Skoric

Abstract:

The paper examines whether the impacts of artificial intelligence (AI) can be meaningfully addressed through the rights-based approach to AI design, investigating in particular how the inclusive, participatory process of assessing the AI impact would make this viable. There is a significant gap between envisioning rights-based AI systems and their practical application. Plausibly, internalizing human rights approach within AI design process might be achieved through identifying and assessing implications of AI features human rights, especially considering the case of vulnerable individuals and communities. However, there is no clarity or consensus on how such an instrument should be operationalised to usefully identify the impact, mitigate harms and meaningfully ensure relevant stakeholders’ participation. In practice, ensuring the meaningful inclusion of those individuals, groups, or entire communities who are affected by the use of the AI system is a prerequisite for a process seeking to assess human rights impacts and risks. Engagement in the entire process of the impact assessment should enable those affected and interested to access information and better understand the technology, product, or service and resulting impacts, but also to learn about their rights and the respective obligations and responsibilities of developers and deployers to protect and/or respect these rights. This paper will provide an overview of the study and practice of the participatory design process for AI, including inclusive impact assessment, its main elements, propose a framework, and discuss the lessons learned from the existing theory. In addition, it will explore pathways for enhancing and promoting individual and group rights through such engagement by discussing when, how, and whom to include, at which stage of the process, and what are the pre-requisites for meaningful and engaging. The overall aim is to ensure using the technology that works for the benefit of society, individuals, and particular (historically marginalised) groups.

Keywords: rights-based design, AI impact assessment, inclusion, harm mitigation

Procedia PDF Downloads 149

Authors: Farid Khosravikia, Patricia Clayton

Abstract:

The main objective of this work is to evaluate the advantages and disadvantages of various machine learning techniques in two key steps of seismic hazard and risk assessment of different types of structures. The first step is the development of ground-motion models, which are used for forecasting ground-motion intensity measures (IM) given source characteristics, source-to-site distance, and local site condition for future events. IMs such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available. Second, it is investigated how machine learning techniques could be beneficial for developing probabilistic seismic demand models (PSDMs), which provide the relationship between the structural demand responses (e.g., component deformations, accelerations, internal forces, etc.) and the ground motion IMs. In the risk framework, such models are used to develop fragility curves estimating exceeding probability of damage for pre-defined limit states, and therefore, control the reliability of the predictions in the risk assessment. In this study, machine learning algorithms like artificial neural network, random forest, and support vector machine are adopted and trained on the demand parameters to derive PSDMs for them. It is observed that such models can provide more accurate estimates of prediction in relatively shorter about of time compared to conventional methods. Moreover, they can be used for sensitivity analysis of fragility curves with respect to many modeling parameters without necessarily requiring more intense numerical response-history analysis.

Keywords: artificial neural network, machine learning, random forest, seismic risk analysis, seismic hazard analysis, support vector machine

Procedia PDF Downloads 101

Authors: Magdi Elmessiry, Adel Elmessiry

Abstract:

The fashion industry represents a significant portion of the global gross domestic product, however, it is plagued by cheap imitators that infringe on the trademarks which destroys the fashion industry's hard work and investment. While eventually the copycats would be found and stopped, the damage has already been done, sales are missed and direct and indirect jobs are lost. The infringer thrives on two main facts: the time it takes to discover them and the lack of tracking technologies that can help the consumer distinguish them. Blockchain technology is a new emerging technology that provides a distributed encrypted immutable and fault resistant ledger. Blockchain presents a ripe technology to resolve the infringement epidemic facing the fashion industry. The significance of the study is that a new approach leveraging the state of the art blockchain technology coupled with artificial intelligence is used to create a framework addressing the fashion infringement problem. It transforms the current focus on legal enforcement, which is difficult at best, to consumer awareness that is far more effective. The framework, Crypto CopyCat, creates an immutable digital asset representing the actual product to empower the customer with a near real time query system. This combination emphasizes the consumer's awareness and appreciation of the product's authenticity, while provides real time feedback to the producer regarding the fake replicas. The main findings of this study are that implementing this approach can delay the fake product penetration of the original product market, thus allowing the original product the time to take advantage of the market. The shift in the fake adoption results in reduced returns, which impedes the copycat market and moves the emphasis to the original product innovation.

Keywords: fashion, infringement, blockchain, artificial intelligence, textiles supply chain

Procedia PDF Downloads 255

Authors: Monika Soni, Chandra Bhattacharya, Siraj Ahmed Ahmed, Prafulla Dutta

Abstract:

Dengue is now a globally important arboviral disease. Extensive vector surveillance has already established A.aegypti as a primary vector, but A.albopictus is now accelerating the situation through gradual adaptation to human surroundings. Global destabilization and gradual climatic shift with rising in temperature have significantly expanded the geographic range of these species These versatile vectors also host Chikungunya, Zika, and yellow fever virus. Biggest challenge faced by endemic countries now is upsurge in co-infection reported with multiple serotypes and virus co-circulation. To foster vector control interventions and mitigate disease burden, there is surge for knowledge on vector susceptibility and viral tolerance in response to multiple infections. To address our understanding on transmission dynamics and reproductive fitness, both the vectors were exposed to single and dual combinations of all four dengue serotypes by artificial feeding and followed up to third generation. Artificial feeding observed significant difference in feeding rate for both the species where A.albopictus was poor artificial feeder (35-50%) compared to A.aegypti (95-97%) Robust sequential screening of viral antigen in mosquitoes was followed by Dengue NS1 ELISA, RT-PCR and Quantitative PCR. To observe viral dissemination in different mosquito tissues Indirect immunofluorescence assay was performed. Result showed that both the vectors were infected initially with all dengue(1-4)serotypes and its co-infection (D1 and D2, D1 and D3, D1 and D4, D2 and D4) combinations. In case of DENV-2 there was significant difference in the peak titer observed at 16th day post infection. But when exposed to dual infections A.aegypti supported all combinations of virus where A.albopictus only continued single infections in successive days. There was a significant negative effect on the fecundity and fertility of both the vectors compared to control (PANOVA < 0.001). In case of dengue 2 infected mosquito, fecundity in parent generation was significantly higher (PBonferroni < 0.001) for A.albopicus compare to A.aegypti but there was a complete loss of fecundity from second to third generation for A.albopictus. It was observed that A.aegypti becomes infected with multiple serotypes frequently even at low viral titres compared to A.albopictus. Possible reason for this could be the presence of wolbachia infection in A.albopictus or mosquito innate immune response, small RNA interference etc. Based on the observations it could be anticipated that transovarial transmission may not be an important phenomenon for clinical disease outcome, due to the absence of viral positivity by third generation. Also, Dengue NS1 ELISA can be used for preliminary viral detection in mosquitoes as more than 90% of the samples were found positive compared to RT-PCR and viral load estimation.

Keywords: co-infection, dengue, reproductive fitness, viral quantification

Procedia PDF Downloads 200

Authors: Chutikarn Sriviboon, Witthaya Mekhum

Abstract:

The purposes of this research were to analyze and evaluate successful factors in OTOP production process for the developing of learning center on OTOP production process based on Sufficiency Economic Philosophy for sustainable life quality. The research has been designed as a qualitative study to gather information from 30 OTOP producers in Bangkontee District, Samudsongkram Province. They were all interviewed on 3 main parts. Part 1 was about the production process including 1) production 2) product development 3) the community strength 4) marketing possibility and 5) product quality. Part 2 evaluated appropriate successful factors including 1) the analysis of the successful factors 2) evaluate the strategy based on Sufficiency Economic Philosophy and 3) the model of learning center on OTOP production process based on Sufficiency Economic Philosophy for sustainable life quality. The results showed that the production did not affect the environment with potential in continuing standard quality production. They used the raw materials in the country. On the aspect of product and community strength in the past 1 year, it was found that there was no appropriate packaging showing product identity according to global market standard. They needed the training on packaging especially for food and drink products. On the aspect of product quality and product specification, it was found that the products were certified by the local OTOP standard. There should be a responsible organization to help the uncertified producers pass the standard. However, there was a problem on food contamination which was hazardous to the consumers. The producers should cooperate with the government sector or educational institutes involving with food processing to reach FDA standard. The results from small group discussion showed that the community expected high education and better standard living. Some problems reported by the community included informal debt and drugs in the community. There were 8 steps in developing the model of learning center on OTOP production process based on Sufficiency Economic Philosophy for sustainable life quality.

Keywords: production process, OTOP, sufficiency economic philosophy, learning center

Procedia PDF Downloads 375

Authors: Meriem El Kolli, Hocine Laouer, Hayet El Kolli, Salah Akkal

Abstract:

The methanolic extract (ME) of C. montanum obtained by a hydo-alcoholic maceration and its polyphenol content was evaluated by Folin-Ciocalteu method. This extract and C. montanum essential oil were screened for antimicrobial activity against 21 microbial strains by agar diffusion method. MICs of the EO were determined by the broth micro dilution method. The mechanism of action of the EO was determined on the susceptible strains by the time kill assay and the lysis experience. Antioxidant properties were studied by both free DPPH radical scavenging and reducing power techniques. The TPC in the ME showed a high level of 101.50 ± 5.33 mg GAE /mg. B. cereus was the most sensitive strain with MIC of 55.5 µg/ml , then K. pneumoniae (111 µg/ml). A remarkable decrease in a survival rate as well as in the absorbance at 260 nm were recorded, which suggest that the cytoplasm membrane is one of the targets of the EO. Antioxidant effects were concentration dependent and IC50 values were 1.09 ± 0.37 µg/ml for the EO and 65.04 ± 0.00 µg/ml for the ME by DPPH method and a reducing power dose-dependent. In conclusion, C. montanum extracts showed potent which could be exploited in the food industry for food preservation.

Keywords: C. montanum, Apiaceae, essential oils, antimicrobial activity, antioxidant activity, reducing power

Procedia PDF Downloads 233

Authors: Raana Babadi Fathipour

Abstract:

Nourishment nanotechnology is an range of rising intrigued and opens up a entirety universe of modern conceivable outcomes for the nourishment industry. The essential categories of nanotechnology applications and functionalities right now within the improvement of nourishment bundling incorporate: the enhancement of plastic materials obstructions, the consolidation of dynamic components that can convey utilitarian properties past those of customary dynamic bundling, and the detecting and signaling of significant data. Nano nourishment bundling materials may amplify nourishment life, move forward nourishment security, alarm buyers that nourishment is sullied or ruined, repair tears in bundling, and indeed release preservatives to expand the life of the nourishment within the bundle. Nanotechnology applications within the nourishment industry can be utilized to identify microbes in bundling, or produce stronger flavors and color quality, and security by expanding the obstruction properties. Nanotechnology holds extraordinary guarantee to supply benefits not fair inside nourishment items but too around nourishment items. In reality, nanotechnology presents modern chances for advancement within the nourishment industry at monstrous speed, but instability and wellbeing concerns are moreover developing. EU/WE/global enactment for the direction of nanotechnology in nourishment are scanty. Besides, current enactment shows up unacceptable to nanotechnology specificity.

Keywords: nano technology, nano foods, food packaging, nano participle

Procedia PDF Downloads 61

Authors: Francis Gbogbo, Angelica Ama Essandoh, Wendy Teresa Baffoe, Henry Groos, Charles Mario Boateng, Emmanuel Robert Blankson

Abstract:

Baseline data on plastic landing by fishers and monitoring of this is important in evaluating the success of plastic waste management efforts. This study investigated plastic and fish landed by beach seine fishers in Ghana, together with the rate of plastic deposition on an adjoining beach. Plastic constituted 31.6% of the total catch, and 41.7% of the fish landed by weight. There were significant differences between the average weight of fish (139.58±53.6kg) and plastic (65.73±14.6kg) landed per fishing session and the catch per unit effort of fish (183.4±76.7 kg/day) and plastic (88.4±35.2 kg/day). The mean weight of plastic landed per fishing session was higher than the mean weight of each of the 26 species of fisheries. The rate of plastic deposition on the beach was 8.1±2.5 plastic items per m2 per tidal cycle or 0.35±0.11kg plastic per m2 per tidal cycle, with food packs and tableware dominating the deposited plastic. The results suggested that ongoing water sachets and plastic bottle recycling in Ghana are yielding results and calls for targeted efforts in plastic food packs and tableware management.

Keywords: fishig, landing, plastic waste, intertidal area, fishing effort

Procedia PDF Downloads 85

Authors: Isaac Kayode Ogunlade

Abstract:

Data acquisition (DAQ) is the process by which physical phenomena from the real world are transformed into an electrical signal(s) that are measured and converted into a digital format for processing, analysis, and storage by a computer. The DAQ is designed using PIC18F4550 microcontroller, communicating with Personal Computer (PC) through USB (Universal Serial Bus). The research deployed initial knowledge of data acquisition system and embedded system to develop a weather data acquisition device using LM35 sensor to measure weather parameters and the use of Artificial Intelligence(Artificial Neural Network - ANN)and statistical approach(Autoregressive Integrated Moving Average – ARIMA) to predict precipitation (rainfall). The device is placed by a standard device in the Department of Meteorology, Federal University of Technology, Akure (FUTA) to know the performance evaluation of the device. Both devices (standard and designed) were subjected to 180 days with the same atmospheric condition for data mining (temperature, relative humidity, and pressure). The acquired data is trained in MATLAB R2012b environment using ANN, and ARIMAto predict precipitation (rainfall). Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Correction Square (R2), and Mean Percentage Error (MPE) was deplored as standardize evaluation to know the performance of the models in the prediction of precipitation. The results from the working of the developed device show that the device has an efficiency of 96% and is also compatible with Personal Computer (PC) and laptops. The simulation result for acquired data shows that ANN models precipitation (rainfall) prediction for two months (May and June 2017) revealed a disparity error of 1.59%; while ARIMA is 2.63%, respectively. The device will be useful in research, practical laboratories, and industrial environments.

Keywords: data acquisition system, design device, weather development, predict precipitation and (FUTA) standard device

Procedia PDF Downloads 86

Authors: Rhadinia Tayag-Relanes, Felina C. Young

Abstract:

This study was conducted to analyze the noodle production process at Yan Hu Food Manufacturing for the basis of production improvement. The study utilized the PDCA approach and record review in the gathering of data for the calendar year 2019 from August to October data of the noodle products miki, canton, and misua. Causal-comparative research was used in this study; it attempts to establish cause-effect relationships among the variables such as descriptive statistics and correlation, both were used to compute the data gathered. The study found that miki, canton, and misua production has different cycle time sets for each production and has different production outputs in every set of its production process and a different number of wastages. The company has not yet established its allowable rejection rate/ wastage; instead, this paper used a 1% wastage limit. The researcher recommended the following: machines used for each process of the noodle product must be consistently maintained and monitored; an assessment of all the production operators by checking their performance statistically based on the output and the machine performance; a root cause analysis for finding the solution must be conducted; and an improvement on the recording system of the input and output of the production process of noodle product should be established to eliminate the poor recording of data.

Keywords: continuous improvement, process, operations, PDCA

Procedia PDF Downloads 63

Authors: Saba Belgheisi

Abstract:

Food packaging, is an important discipline in the area of food technology, concerns preservation and protection of foods. The objective of this research was to determine of the effect of whey protein based edible coating on the moisture loss and sensory attributes of fresh mutton after 0, 1, 3 and 5 days at 5° C. The moisture content, moisture loss and sensory attributes (juiciness, color and odor) of the coated and uncoated samples were analyzed. The results showed that, moisture content, moisture loss, juiciness and color of the coated and uncoated samples have significant differences (p < 0.05) at the intervals of 0 to 1 and 1 to 3 days of storage. But no significant difference was observed at interval time 3 to 5 days of storage (p > 0.05). Also, there was no significant differences in the odor values of the coated and uncoated samples (p > 0.05). Therefore, the coated samples had consistently more moisture, juiciness and colored values than uncoated samples after 3 days at 5° C. So, whey protein edible coating could enhance product presentation and eliminate the need for placing absorbent pads at the bottom of the trays.

Keywords: coating, whey protein, mutton, moisture, sensory

Procedia PDF Downloads 459

Authors: Salami Abiodun Olusola, Bankole Faith Ayobami

Abstract:

Agro-wastes are wastes produced from various agricultural activities and include manures, corncob, plant stalks, hulls, leaves, sugarcane bagasse, oil-palm spadix, and rice bran. In farming situation, the agro-waste is often useless and, thus, discarded. Huge quantities of waste resources generated from Nigerian agriculture could be converted to more useful forms of energy, which could contribute to the country’s primary energy needs and reduce problems associated with waste management. Accumulation of agro-wastes may cause health, safety, and environmental concern. However, biotechnological use of agro-waste could enhance food security through its bioconversion to useful renewable energy. Mushrooms are saprophytes which feed by secreting extracellular enzymes, digesting food externally, and absorb the nutrients in net-like hyphae. Therefore, mushrooms could be exploited for bioconversion of the cheap and numerous agro-wastes for providing nutritious food for animals, human and carbon recycling. The study investigated the bioconversion potentials of Pleurotus florida on agro-wastes using a simple and cost-effective biotechnological method. Four agro-wastes; corncobs, oil-palm spadix, corn straw, and sawdust, were composted and used as substrates while the biological efficiency (BE) and the nutritional composition of P. florida grown on the substrates were determined. Pleurotus florida contained 26.28-29.91% protein, 86.90-89.60% moisture, 0.48-0.91% fat, 19.64-22.82% fibre, 31.37-38.17% carbohydrate and 5.18-6.39% ash. The mineral contents ranged from 342-410 mg/100g Calcium, 1009-1133 mg/100g Phosphorus, 17-21 mg/100g Iron, 277-359 mg/100g Sodium, and 2088-2281 mg/100g Potassium. The highest yield and BE were obtained on corncobs (110 g, 55%), followed by oil-palm spadix (76.05 g, 38%), while the least BE was recorded on corn straw substrate (63.12 g, 31.56%). Utilization of the composted substrates yielded nutritional and edible mushrooms. The study presents biotechnological procedure for bioconversion of agro-wastes to edible and nutritious mushroom for efficient agro-wastes’ management, utilization, and recycling.

Keywords: agrowaste, bioconversion, biotechnology, utilization, recycling

Procedia PDF Downloads 73

Authors: Magdalena Maria Rost-Roszkowska, Alina Chachulska-Żymełka, Monika Tarnawska, Maria Augustyniak, Alina Kafel, Agnieszka Babczyńska

Abstract:

The digestive system of insects is composed of three distinct regions: fore-, mid- and hingut. The middle region (the midgut) is treated as one of the barriers which protects the organism against any stressors which originate from external environment, e.g. toxic metals. Such factors can activate the cell death in epithelial cells to preserve the entire tissue/organs against the degeneration. Different mechanisms involved in homeostasis maintenance have been described, but the studies of animals under field conditions do not give the opportunity to conclude about potential ability of subsequent generation to inherit the tolerance mechanisms. It is possible only by a multigenerational strain of an animal led under laboratory conditions, exposed to a selected toxic factor, present also in polluted ecosystems. The main purpose of the project was to check if changes, which appear in the midgut epithelium after Cd treatment, can be fixed during the following generations of insects with the special emphasis on apoptosis. As the animal for these studies we chose 5th larval stage of the beet armyworm Spodoptera exigua Hübner (Lepidoptera: Noctuidae), which is one of pest of many vegetable crops. Animals were divided into some experimental groups: K, Cd, KCd, Cd1, Cd2, Cd3. A control group (K) fed a standard diet, and was conducted for XX generations, a cadmium group (Cd), fed on standard diet supplemented with cadmium (44 mg Cd per kg of dry weight of food) for XXX generations. A reference Cd group (KCd) has been initiated: control insects were fed with Cd supplemented diet (44 mg Cd per kg of dry weight of food). Experimental groups Cd1, Cd2, Cd3 developed from the control one: 5 mg Cd per kg of dry weight of food, 10 mg Cd per kg of dry weight of food, 20 mg Cd per kg of dry weight of food. We were interested in the activation of apoptosis during following generations in all experimental groups. Therefore, during the 1st year of the experiment, the measurements were done for 6 generations in all experimental group. The intensity and the course of apoptosis have been examined using transmission electron microscope (TEM), confocal microscope and flow cytometry. During apoptosis the cell started to shrink, extracellular spaces appeared between digestive and neighboring cells, the nucleus achieved a lobular shape. Eventually, the apoptotic cells was discharged into the midgut lumen. A quantitative analysis revealed that the number of apoptotic cells depends significantly on the generation, tissue and cadmium concentration in the insect rearing medium. In the following 6 generations, we observed that the percentage of apoptotic cells in the midguts from cadmium-exposed groups decreased gradually according to the following order of strains: Cd1, Cd2, Cd3 and KCd. At the same time, it was still higher than the percentage of apoptotic cells in the same tissues of the insects from the control and multigenerational cadmium strain. The results of our studies suggest that changes caused by cadmium treatment were preserved during 6-generational development of lepidopteran larvae. The study has been financed by the National Science Centre Poland, grant no 2016/21/B/NZ8/00831.

Keywords: cadmium, cell death, digestive system, ultrastructure

Procedia PDF Downloads 209

Authors: M. Naimi, M. B. Khaled

Abstract:

The aim of the present work was to test in vitro inhibition of food pathogens and spoilage bacteria by crude bacteriocins from autochthonous lactic acid bacteria. Thirty autochthonous lactic acid bacteria isolated previously, belonging to the genera: Lactobacillus, Carnobacterium, Lactococcus, Vagococcus, Streptococcus, and Pediococcus, have been screened by an agar spot test and a well diffusion assay against Gram-positive and Gram-negative harmful bacteria: Bacillus cereus, Bacillus subtilis ATCC 6633, Escherichia coli ATCC 8739, Salmonella typhimurium ATCC 14028, Staphylococcus aureus ATCC 6538, and Pseudomonas aeruginosa under conditions means to reduce lactic acid and hydrogen peroxide effect to select bacteria with high bacteriocinogenic potential. Furthermore, crude bacteriocins semiquantification and heat sensitivity to different temperatures (80, 95, 110°C, and 121°C) were performed. Another exploratory test concerning the response of St. aureus ATCC 6538 to the presence of crude bacteriocins was realized. It has been observed by the agar spot test that fifteen candidates were active toward Gram-positive targets strains. The secondary screening demonstrated an antagonistic activity oriented only against St. aureus ATCC 6538, leading to the selection of five isolates: Lm14, Lm21, Lm23, Lm24, and Lm25 with a larger inhibition zone compared to the others. The ANOVA statistical analysis reveals a small variation of repeatability: Lm21: 0.56%, Lm23: 0%, Lm25: 1.67%, Lm14: 1.88%, Lm24: 2.14%. Conversely, slight variation was reported in terms of inhibition diameters: 9.58± 0.40, 9.83± 0.46, and 10.16± 0.24 8.5 ± 0.40 10 mm for, Lm21, Lm23, Lm25, Lm14and Lm24, indicating that the observed potential showed a heterogeneous distribution (BMS = 0.383, WMS = 0.117). The repeatability coefficient calculated displayed 7.35%. As for the bacteriocins semiquantification, the five samples exhibited production amounts about 4.16 for Lm21, Lm23, Lm25 and 2.08 AU/ml for Lm14, Lm24. Concerning the sensitivity the crude bacteriocins were fully insensitive to heat inactivation, until 121°C, they preserved the same inhibition diameter. As to, kinetic of growth , the µmax showed reductions in pathogens load for Lm21, Lm23, Lm25, Lm14, Lm24 of about 42.92%, 84.12%, 88.55%, 54.95%, 29.97% in the second trails. Inversely, this pathogen growth after five hours displayed differences of 79.45%, 12.64%, 11.82%, 87.88%, 85.66% in the second trails, compared to the control. This study showed potential inhibition to the growth of this food pathogen, suggesting the possibility to improve the hygienic food quality.

Keywords: exploratory test, lactic acid bacteria, crude bacteriocins, spoilage, pathogens

Procedia PDF Downloads 210

Authors: M. Sarraf, J. E. Moros, M. C. Sánchez

Abstract:

Oleogels are self-standing systems that are able to trap edible liquid oil into a tridimensional network and also help to use less fat by forming crystallization oleogelators. There are different ways to generate oleogelation and oil structuring, including direct dispersion, structured biphasic systems, oil sorption, and indirect method (emulsion-template). The selection of processing conditions as well as the composition of the oleogels is essential to obtain a stable oleogel with characteristics suitable for its purpose. In this sense, one of the ingredients widely used in food products to produce oleogels and emulsions is polysaccharides. Basil seed gum (BSG), with the scientific name Ocimum basilicum, is a new native polysaccharide with high viscosity and pseudoplastic behavior because of its high molecular weight in the food industry. Also, proteins can stabilize oil in water due to the presence of amino and carboxyl moieties that result in surface activity. Whey proteins are widely used in the food industry due to available, cheap ingredients, nutritional and functional characteristics such as emulsifier and a gelling agent, thickening, and water-binding capacity. In general, the interaction of protein and polysaccharides has a significant effect on the food structures and their stability, like the texture of dairy products, by controlling the interactions in macromolecular systems. Using edible oleogels as oil structuring helps for targeted delivery of a component trapped in a structural network. Therefore, the development of efficient oleogel is essential in the food industry. A complete understanding of the important points, such as the ratio oil phase, processing conditions, and concentrations of biopolymers that affect the formation and stability of the emulsion, can result in crucial information in the production of a suitable oleogel. In this research, the effects of oil concentration and pressure used in the manufacture of the emulsion prior to obtaining the oleogel have been evaluated through the analysis of droplet size and rheological properties of obtained emulsions and oleogels. The results show that the emulsion prepared in the high-pressure homogenizer (HPH) at higher pressure values has smaller droplet sizes and a higher uniformity in the size distribution curve. On the other hand, in relation to the rheological characteristics of the emulsions and oleogels obtained, the predominantly elastic character of the systems must be noted, as they present values of the storage modulus higher than those of losses, also showing an important plateau zone, typical of structured systems. In the same way, if steady-state viscous flow tests have been analyzed on both emulsions and oleogels, the result is that, once again, the pressure used in the homogenizer is an important factor for obtaining emulsions with adequate droplet size and the subsequent oleogel. Thus, various routes for trapping oil inside a biopolymer matrix with adjustable mechanical properties could be applied for the creation of the three-dimensional network in order to the oil absorption and creating oleogel.

Keywords: basil seed gum, particle size, viscoelastic properties, whey protein

Procedia PDF Downloads 62

Authors: Bulent Topcuoglu

Abstract:

Repeated amendments of organic matter and intensive use of fertilizers, metal-enriched chemicals and biocides may cause soil and environmental pollution in greenhouses. Specially, the impact of heavy metal pollution of soils on food metal content and underground water quality has become a public concern. Due to potential toxicity of heavy metals to human life and environment, determining the chemical form of heavy metals in greenhouse soils is an important approach of chemical characterization and can provide useful information on its mobility and bioavailability. A sequential extraction procedure was used to estimate the availability of heavy metals (Zn, Cd, Ni, Pb and Cr) in greenhouse soils of Antalya Aksu. Zn was predominantly associated with Fe-Mn oxide fraction, major portion of Cd associated with carbonate and organic matter fraction, a major portion of (>65 %) Ni and Cr were largely associated with Fe-Mn oxide and residual fractions and Pb was largely associated with organic matter and Fe-Mn oxide fractions. Results of the present study suggest that the mobility and bioavailability of metals probably increase in the following order: Cr < Pb < Ni < Cd < Zn. Among the elements studied, Zn and Cd appeared to be the most readily soluble and potentially bioavailable metals and these metals may carry a potential risk for metal transfer in food chain and contamination to ground water.

Keywords: metal speciation, metal mobility, greenhouse soils, biosystems engineering

Procedia PDF Downloads 410

Authors: Aprajeeta Jha, Punyadarshini P. Tripathy

Abstract:

Drying technologies for various food processing operations shares an inevitable linkage with energy, cost and environmental sustainability. Hence, solar drying of food grains has become imperative choice to combat duo challenges of meeting high energy demand for drying and to address climate change scenario. But performance and reliability of solar dryers depend hugely on sunshine period, climatic conditions, therefore, offer a limited control over drying conditions and have lower efficiencies. Solar drying technology, supported by Photovoltaic (PV) power plant and hybrid type solar air collector can potentially overpower the disadvantages of solar dryers. For development of such robust hybrid dryers; to ensure quality and shelf-life of paddy grains the optimization of process parameter becomes extremely critical. Investigation of the moisture distribution profile within the grains becomes necessary in order to avoid over drying or under drying of food grains in hybrid solar dryer. Computational simulations based on finite element modeling can serve as potential tool in providing a better insight of moisture migration during drying process. Hence, present work aims at optimizing the process parameters and to develop a 3-dimensional (3D) finite element model (FEM) for predicting moisture profile in paddy during solar drying. COMSOL Multiphysics was employed to develop a 3D finite element model for predicting moisture profile. Furthermore, optimization of process parameters (power level, air velocity and moisture content) was done using response surface methodology in design expert software. 3D finite element model (FEM) for predicting moisture migration in single kernel for every time step has been developed and validated with experimental data. The mean absolute error (MAE), mean relative error (MRE) and standard error (SE) were found to be 0.003, 0.0531 and 0.0007, respectively, indicating close agreement of model with experimental results. Furthermore, optimized process parameters for drying paddy were found to be 700 W, 2.75 m/s at 13% (wb) with optimum temperature, milling yield and drying time of 42˚C, 62%, 86 min respectively, having desirability of 0.905. Above optimized conditions can be successfully used to dry paddy in PV integrated solar dryer in order to attain maximum uniformity, quality and yield of product. PV-integrated hybrid solar dryers can be employed as potential and cutting edge drying technology alternative for sustainable energy and food security.

Keywords: finite element modeling, moisture migration, paddy grain, process optimization, PV integrated hybrid solar dryer

Procedia PDF Downloads 147

Authors: Sara Tokhi Arab, Rozo Noguchi, Tofeal Ahamed

Abstract:

Drought is a natural disaster that occurs in a region due to a lack of precipitation and high temperatures over a continuous period or in a single season as a consequence of climate change. Precipitation deficits and prolonged high temperatures mostly affect the agricultural sector, water resources, socioeconomics, and the environment. Consequently, it causes agricultural product loss, food shortage, famines, migration, and natural resources degradation in a region. Agriculture is the first sector affected by drought. Therefore, it is important to develop an agricultural drought risk and loss assessment to mitigate the drought impact in the agriculture sector. In this context, the main purpose of this study was to assess yield loss using composite drought indices in the drought-affected vineyards. In this study, the CDI was developed for the years 2016 to 2020 by comprising five indices: the vegetation condition index (VCI), temperature condition index (TCI), deviation of NDVI from the long-term mean (NDVI DEV), normalized difference moisture index (NDMI) and precipitation condition index (PCI). Moreover, the quantitative principal component analysis (PCA) approach was used to assign a weight for each input parameter, and then the weights of all the indices were combined into one composite drought index. Finally, Bayesian regularized artificial neural networks (BRANNs) were used to evaluate the yield variation in each affected vineyard. The composite drought index result indicated the moderate to severe droughts were observed across the Kabul Province during 2016 and 2018. Moreover, the results showed that there was no vineyard in extreme drought conditions. Therefore, we only considered the severe and moderated condition. According to the BRANNs results R=0.87 and R=0.94 in severe drought conditions for the years of 2016 and 2018 and the R= 0.85 and R=0.91 in moderate drought conditions for the years of 2016 and 2018, respectively. In the Kabul Province within the two years drought periods, there was a significate deficit in the vineyards. According to the findings, 2018 had the highest rate of loss almost -7 ton/ha. However, in 2016 the loss rates were about – 1.2 ton/ha. This research will support stakeholders to identify drought affect vineyards and support farmers during severe drought.

Keywords: grapes, composite drought index, yield loss, satellite remote sensing

Procedia PDF Downloads 152

Authors: Nguyen J. M., Lucas G., Ruan S., Digonnet H., Antonioli D.

Abstract:

Introduction: Deep Learning (DL) is a very powerful tool for analyzing image data. But for tabular data, it cannot compete with machine learning methods like XGBoost. The research question becomes: can tabular data be transformed into images that can be analyzed by simple CNNs (Convolutional Neuron Networks)? Will DL be the absolute tool for data classification? All current solutions consist in repositioning the variables in a 2x2 matrix using their correlation proximity. In doing so, it obtains an image whose pixels are the variables. We implement a technology, DeepNIC, that offers the possibility of obtaining an image for each variable, which can be analyzed by simple CNNs. Material and method: The 'ROP' (Regression OPtimized) model is a binary and atypical decision tree whose nodes are managed by a new artificial neuron, the Neurop. By positioning an artificial neuron in each node of the decision trees, it is possible to make an adjustment on a theoretically infinite number of variables at each node. From this new decision tree whose nodes are artificial neurons, we created the concept of a 'Random Forest of Perfect Trees' (RFPT), which disobeys Breiman's concepts by assembling very large numbers of small trees with no classification errors. From the results of the RFPT, we developed a family of 10 statistical information criteria, Nguyen Information Criterion (NICs), which evaluates in 3 dimensions the predictive quality of a variable: Performance, Complexity and Multiplicity of solution. A NIC is a probability that can be transformed into a grey level. The value of a NIC depends essentially on 2 super parameters used in Neurops. By varying these 2 super parameters, we obtain a 2x2 matrix of probabilities for each NIC. We can combine these 10 NICs with the functions AND, OR, and XOR. The total number of combinations is greater than 100,000. In total, we obtain for each variable an image of at least 1166x1167 pixels. The intensity of the pixels is proportional to the probability of the associated NIC. The color depends on the associated NIC. This image actually contains considerable information about the ability of the variable to make the prediction of Y, depending on the presence or absence of other variables. A basic CNNs model was trained for supervised classification. Results: The first results are impressive. Using the GSE22513 public data (Omic data set of markers of Taxane Sensitivity in Breast Cancer), DEEPNic outperformed other statistical methods, including XGBoost. We still need to generalize the comparison on several databases. Conclusion: The ability to transform any tabular variable into an image offers the possibility of merging image and tabular information in the same format. This opens up great perspectives in the analysis of metadata.

Keywords: tabular data, CNNs, NICs, DeepNICs, random forest of perfect trees, classification

Procedia PDF Downloads 118