Search results for: imbalanced fertilization

Authors: Theresa K., Shanmugasundaram R., Kennedy J. S.

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Nutrient supplements are indispensable for raising crops and to reap determining productivity. The nutrient imbalance between replenishment and crop uptake is attempted through the input of inorganic fertilizers. Excessive dumping of inorganic nutrients in soil cause stagnant and decline in yield. Imbalanced N-P-K ratio in the soil exacerbates and agitates the soil ecosystems. The study evaluated the fertilization practices of conventional (CFs), organic and Integrated Nutrient Management system (INM) on soil quality using key indicators and soil quality indices. Twelve rice farming fields of which, ten fields were having conventional cultivation practices, one field each was organic farming based and INM based cultivated under monocropping sequence in the Thondamuthur block of Coimbatore district were fixed and properties viz., physical, chemical and biological were studied for four cropping seasons to determine soil quality index (SQI). SQI was computed for conventional, organic and INM fields. Comparing conventional farming (CF) with organic and INM, CF was recorded with a lower soil quality index. While in organic and INM fields, the higher SQI value of 0.99 and 0.88 respectively were registered. CF₄ received with a super-optimal dose of N (250%) showed a lesser SQI value (0.573) as well as the yield (3.20 t ha⁻¹) and the CF6 which received 125 % N recorded the highest SQI (0.715) and yield (6.20 t ha⁻¹). Likewise, most of the CFs received higher N beyond the level of 125 % except CF₃ and CF₉, which recorded lower yields. CFs which received super-optimal P in the order of CF₆&CF₇>CF₁&CF₁₀ recorded lesser yields except for CF₆. Super-optimal K application also recorded lesser yield in CF₄, CF₇ and CF₉.

Keywords: rice cropping system, soil quality indicators, imbalanced fertilization, yield

Procedia PDF Downloads 122

Authors: Alicja Sułek, Grażyna Cacak-Pietrzak, Marta Wyzińska, Anna Nieróbca

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In 2013/2014 and 2014/2015, a field experiment was conducted in two locations: Osiny and Wielichowo (Poland). The two-factor experiment was based on the method of randomized subblocks, in three replications. The first factor (A) was dose of nitrogen fertilization (two levels). The second factor (B) was nine winter wheat cultivars. It was found that winter wheat cultivars exhibited different reactions to higher nitrogen fertilization depending on the years and localities. Only KWS Dacanto cultivar under all growing conditions showed a significant increase in grain yield after the application of a higher level of nitrogen fertilization. The increase in nitrogen fertilization influenced the increase in gluten proteins content in wheat grain, but these changes were statistically significant only in the first year of the study. The quality of gluten does not depend on nitrogen fertilization. The quality of wheat grain depends on cultivars.

Keywords: fertilization, grain quality, winter wheat, yield

Procedia PDF Downloads 168

Authors: Ansong Richard Omari, Yosei Oikawa, Yoshiharu Fujii, Dorothea Sonoko Bellingrath-Kimura

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Renewed interest in soil management aimed at improving the productive capacity of Sub Saharan Africa (SSA) soils has called for the need to analyse the long term effect of different fertilization systems on soil. This study was conducted in two agroecological zones (i.e., Guinea Savannah (GS) and Deciduous forest (DF)) of Ghana to evaluate the impacts of long term (> 5 years) fertilization schemes on soil chemical and microbial properties. Soil samples under four different fertilization schemes (inorganic, inorganic and organic, organic, and no fertilization) were collected from 20 farmers` field in both agroecological zones. Soil analyses were conducted using standard procedures. All average soil quality parameters except extractable C, potential mineralizable nitrogen and CEC were significantly higher in DF sites compared to GS. Inorganic fertilization proved superior in soil chemical and microbial biomass especially in GS zone. In GS, soil deterioration index (DI) revealed that soil quality deteriorated significantly (−26%) under only organic fertilization system whereas soil improvement was observed under inorganic and no fertilization sites. In DF, either inorganic or organic and inorganic fertilization showed significant positive effects on soil quality. The high soil chemical composition and enhanced microbial biomass in DF were associated with the high rate of inorganic fertilization.

Keywords: deterioration index, fertilization scheme, microbial biomass, tropical agroecological zone

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Authors: Najmeh Abedzadeh, Matthew Jacobs

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An intrusion detection system (IDS) is a software application that monitors malicious activities and generates alerts if any are detected. However, most network activities in IDS datasets are normal, and the relatively few numbers of attacks make the available data imbalanced. Consequently, cyber-attacks can hide inside a large number of normal activities, and machine learning algorithms have difficulty learning and classifying the data correctly. In this paper, a comprehensive literature review is conducted on different types of algorithms for both implementing the IDS and methods in correcting the imbalanced IDS dataset. The most famous algorithms are machine learning (ML), deep learning (DL), synthetic minority over-sampling technique (SMOTE), and reinforcement learning (RL). Most of the research use the CSE-CIC-IDS2017, CSE-CIC-IDS2018, and NSL-KDD datasets for evaluating their algorithms.

Keywords: IDS, imbalanced datasets, sampling algorithms, big data

Procedia PDF Downloads 279

Authors: Ruchika Malhotra, Megha Khanna

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The development of change prediction models can help the software practitioners in planning testing and inspection resources at early phases of software development. However, a major challenge faced during the training process of any classification model is the imbalanced nature of the software quality data. A data with very few minority outcome categories leads to inefficient learning process and a classification model developed from the imbalanced data generally does not predict these minority categories correctly. Thus, for a given dataset, a minority of classes may be change prone whereas a majority of classes may be non-change prone. This study explores various alternatives for adeptly handling the imbalanced software quality data using different sampling methods and effective MetaCost learners. The study also analyzes and justifies the use of different performance metrics while dealing with the imbalanced data. In order to empirically validate different alternatives, the study uses change data from three application packages of open-source Android data set and evaluates the performance of six different machine learning techniques. The results of the study indicate extensive improvement in the performance of the classification models when using resampling method and robust performance measures.

Keywords: change proneness, empirical validation, imbalanced learning, machine learning techniques, object-oriented metrics

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Authors: Kamel Belammi, Houria Fatrim

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imbalanced data set, a problem often found in real world application, can cause seriously negative effect on classification performance of machine learning algorithms. There have been many attempts at dealing with classification of imbalanced data sets. In medical diagnosis classification, we often face the imbalanced number of data samples between the classes in which there are not enough samples in rare classes. In this paper, we proposed a learning method based on a cost sensitive extension of Least Mean Square (LMS) algorithm that penalizes errors of different samples with different weight and some rules of thumb to determine those weights. After the balancing phase, we applythe different classifiers (support vector machine (SVM), k- nearest neighbor (KNN) and multilayer neuronal networks (MNN)) for balanced data set. We have also compared the obtained results before and after balancing method.

Keywords: multilayer neural networks, k- nearest neighbor, support vector machine, imbalanced medical data, least mean square algorithm, diabetes

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Authors: Ekta Jain, Kalpana Dahiya, Vanita Verma

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This paper discusses a priority based imbalanced time minimization assignment problem dealing with the allocation of n jobs to m < n persons in which the project is carried out in two stages, viz. Stage-I and Stage-II. Stage-I consists of n1 ( < m) primary jobs and Stage-II consists of remaining (n-n1) secondary jobs which are commenced only after primary jobs are finished. Each job is to be allocated to exactly one person, and each person has to do at least one job. It is assumed that nature of the Stage-I jobs is such that one person can do exactly one primary job whereas a person can do more than one secondary job in Stage-II. In a particular stage, all persons start doing the jobs simultaneously, but if a person is doing more than one job, he does them one after the other in any order. The aim of the proposed study is to find the feasible assignment which minimizes the total time for the two stage execution of the project. For this, an iterative algorithm is proposed, which at each iteration, solves a constrained imbalanced time minimization assignment problem to generate a pair of Stage-I and Stage-II times. For solving this constrained problem, an algorithm is developed in the current paper. Later, alternate combinations based method to solve the priority based imbalanced problem is also discussed and a comparative study is carried out. Numerical illustrations are provided in support of the theory.

Keywords: assignment, imbalanced, priority, time minimization

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Authors: Hankyu Lee, Seoung Bum Kim

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The issue with imbalance and overlapping in the class distribution becomes important in various applications of data mining. The imbalanced dataset is a special case in classification problems in which the number of observations of one class (i.e., major class) heavily exceeds the number of observations of the other class (i.e., minor class). Overlapped dataset is the case where many observations are shared together between the two classes. Imbalanced and overlapped data can be frequently found in many real examples including fraud and abuse patients in healthcare, quality prediction in manufacturing, text classification, oil spill detection, remote sensing, and so on. The class imbalance and overlap problem is the challenging issue because this situation degrades the performance of most of the standard classification algorithms. In this study, we propose a classification procedure that can effectively handle imbalanced and overlapped datasets by splitting data space into three parts: nonoverlapping, light overlapping, and severe overlapping and applying the classification algorithm in each part. These three parts were determined based on the Hausdorff distance and the margin of the modified support vector machine. An experiments study was conducted to examine the properties of the proposed method and compared it with other classification algorithms. The results showed that the proposed method outperformed the competitors under various imbalanced and overlapped situations. Moreover, the applicability of the proposed method was demonstrated through the experiment with real data.

Keywords: classification, imbalanced data with class overlap, split data space, support vector machine

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Authors: Alvaro Callejas-Ramos, Lorena Alvarez-Perez, Alexander Benitez-Buenache, Anibal R. Figueiras-Vidal

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This contribution presents a promising formulation which allows to extend the principled binary rebalancing procedures, also known as neutral re-balancing mechanisms in the sense that they do not alter the likelihood ratio

Keywords: Bregman divergences, imbalanced multiclass classifi-cation, informed re-balancing, invariant likelihood ratio

Procedia PDF Downloads 180

Authors: Y. Cochet, A. Achim, Tom Flatman, J-C. Domec, J. Ogée, L. Wingate, Ram Oren

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It is accepted that atmospheric CO2 concentration will increase in the future. For the past 30 years, researchers have used FACE (Free-Air Carbon Dioxide Enrichment) facilities to study the development of terrestrial ecosystems under elevated CO2 (eCO2). Forest responses to eCO2 are likely to impact timber industries with potential feedbacks towards the atmosphere. The main objectives of this study were to examine whether eCO2 alone or in combination with N-fertilization alter wood properties and to identify changes in wood anatomy related to water transport. Wood disks were sampled at breast height from mature loblolly pine trees (Pinus taeda L.) harvested at the Duke FACE site (NC, USA). By measuring ring width and intra-ring changes in density (X-ray densitometry) and tracheid size (lumen and cell wall thickness) from pith to bark, the following hypotheses were tested: 1) eCO2 and N-fertilization interact positively to increase significantly above-ground primary productivity; 2) eCO2 and N-fertilization lead to a decrease in density; 3) eCO2 and N-fertilization increase lumen diameter and decrease cell wall thickness, thus affecting water transport capacity. Our results revealed a boost in earlywood tracheid production induced by eCO2 lasting a few years. The following decrease seemed to be buffered by N-fertilization. X-ray profiles did not show a marked decrease in wood density under eCO2 or N-fertilization, although there were changes in cell anatomical properties such as a reduction in cell-wall thickness and an increase in lumen diameter. If such effects of eCO2 are confirmed, forest management strategies for example N-fertilization should be redesigned.

Keywords: wood density, Duke FACE (free-air carbon dioxide enrichment), N fertilization, tree ring

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Authors: Jinyan Li, Simon Fong, Raymond Wong, Mohammed Sabah, Fiaidhi Jinan

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Clinical data analysis and forecasting have make great contributions to disease control, prevention and detection. However, such data usually suffer from highly unbalanced samples in class distributions. In this paper, we target at the binary imbalanced dataset, where the positive samples take up only the minority. We investigate two different meta-heuristic algorithms, particle swarm optimization and bat-inspired algorithm, and combine both of them with the synthetic minority over-sampling technique (SMOTE) for processing the datasets. One approach is to process the full dataset as a whole. The other is to split up the dataset and adaptively process it one segment at a time. The experimental results reveal that while the performance improvements obtained by the former methods are not scalable to larger data scales, the later one, which we call Adaptive Swarm Balancing Algorithms, leads to significant efficiency and effectiveness improvements on large datasets. We also find it more consistent with the practice of the typical large imbalanced medical datasets. We further use the meta-heuristic algorithms to optimize two key parameters of SMOTE. Leading to more credible performances of the classifier, and shortening the running time compared with the brute-force method.

Keywords: Imbalanced dataset, meta-heuristic algorithm, SMOTE, big data

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Authors: Oqba Basal, Andras Szabo

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Using mineral fertilization is increasing worldwide, as it is claimed to be majorly responsible for achieving high yields; however, the negative impacts of mineral fertilization on soil and environment are becoming more obvious, with alternative methods being more necessary and applicable, especially with the current climatic changes which have imposed serious abiotic stresses, such as drought. An experiment was made during 2017 growing season in Debrecen, Hungary to investigate the effects of inoculation and N fertilization on the seed yield and protein concentration of the soybean (Glycine max (L.) Merr.) cultivar (Panonia Kincse) under three different irrigation regimes: severe drought stress (SD), moderate drought stress (MD) and control with no drought stress (ND). Three N fertilizer rates were applied: no N fertilizer (0 N), 35 kg ha⁻¹ of N fertilizer (35 N) and 105 kg ha⁻¹ of N fertilizer (105 N). Half of the seeds in each treatment was inoculated with Bradyrhizobium japonicum inoculant, and the other half was not inoculated. The results showed significant differences in the seed yield associated with inoculation, irrigation and the interaction between them, whereas there were no significant differences in the seed yield associated with fertilization alone or in interaction with inoculation or irrigation or both. When seeds were inoculated, yield was increased when (35 N) was applied compared to (0 N) but not significantly; however, the high rate of N fertilizer (105 N) reduced the yield to a level even less than (0 N). When seeds were not inoculated, the highest rate of N increased the yield the most compared to the other two N fertilizer rates whenever the drought was present (moderate or severe). Under severe drought stress, inoculation was positively and significantly correlated with yield; however, adding N fertilizer increased the yield of uninoculated plants compared to the inoculated ones, regardless of the rate of N fertilizer. Protein concentration in the seeds was significantly affected by irrigation and by fertilization, but not by inoculation. Protein concentration increased as the N fertilization rate increased, regardless of the inoculation or irrigation treatments; moreover, increasing the N rate reduced the correlation coefficient of protein concentration with the irrigation. It was concluded that adding N fertilizer is not always recommended, especially when seeds are inoculated before being sown; however, it is very important under severe drought stress to sustain yield. Enhanced protein concentrations could be achieved by applying N fertilization, whether the seeds were pre-inoculated or not.

Keywords: drought stress, N fertilization, protein concentration, soybean

Procedia PDF Downloads 125

Authors: Laila Nassiri, Aziza Irhza, Jamal Ibijbijen, Fouad Rachidi, Ghizlane Echchgadda

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The introduction of agroecological practices in ecosystems can contribute to meeting the challenges posed by the diversion of current agricultural production systems towards efficient production methods that are more respectful of the environment, including a reasoned use of inputs and resources. Intercropping is one of these practices that requires the production of two or more crops on the same plot and during the same growing season. Organic fertilization also can contribute to increase the yield due to the potential availability of nutrients. The objective of this work is to study the effect of intercropping and organic fertilization, which are two important practices of agroecology, on potato yield. Intercropping of potato and faba bean was carried out at the Agroecology and Environment platform (ENA, Meknes). The soil is silty-clay, the climate is warm with an average temperature of 17.1°C, and the annual average rainfall of 511mm. Four treatments were tested: Potato sole crop (T1), potato + organic fertilization (T2), Potato + faba bean (T3), Potato + faba bean + organic fertilization (T4). The results showed that there is a significant effect of the treatment on the evolution of the agronomical characters studied, especially the number of leaves and the yield. The number of stems at t0 was equal to 1 in all treatments; it began to grow after 30 days from the date of sowing with a slight increase in treatments containing organic fertilization (T2-T4), then it stabilized 60 days after sowing. In terms of the mean value of the number of leaves, a significant difference was noted between the treatments, the highest value was recorded in treatment T2. The T2 treatment showed the highest average yield, followed by the control (T1). As for the yield, treatments T2 and T1 recorded the highest number of tubers. In order to evaluate two of the practices of agroecology, this work focuses on the evaluation of the effect of intercropping and organic fertilization on the growth and yield parameters of the potato. The results obtained show that agroecological practices have a significant effect on the measured parameters.

Keywords: agroecology, intercropping, organic fertilization, potato yield

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Authors: Saba Ebrahimi, Saeed Ahmadian, Hedie Ashrafi

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Selecting appropriate patients for surgery is one of the main issues in thoracic surgery (TS). Both short-term and long-term risks and benefits of surgery must be considered in the patient selection criteria. There are some limitations in the existing datasets of TS patients because of missing values of attributes and imbalanced distribution of survival classes. In this study, a novel ensemble architecture of deep learning networks is proposed based on stacking different linear and non-linear layers to deal with imbalance datasets. The categorical and numerical features are split using different layers with ability to shrink the unnecessary features. Then, after extracting the insight from the raw features, a novel biased-kernel layer is applied to reinforce the gradient of the minority class and cause the network to be trained better comparing the current methods. Finally, the performance and advantages of our proposed model over the existing models are examined for predicting patient survival after thoracic surgery using a real-life clinical data for lung cancer patients.

Keywords: deep learning, ensemble models, imbalanced classification, lung cancer, TS patient selection

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Authors: Salma El Hajjami, Jamal Malki, Alain Bouju, Mohammed Berrada

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With the expansion of machine learning and data mining in the context of Big Data analytics, the common problem that affects data is class imbalance. It refers to an imbalanced distribution of instances belonging to each class. This problem is present in many real world applications such as fraud detection, network intrusion detection, medical diagnostics, etc. In these cases, data instances labeled negatively are significantly more numerous than the instances labeled positively. When this difference is too large, the learning system may face difficulty when tackling this problem, since it is initially designed to work in relatively balanced class distribution scenarios. Another important problem, which usually accompanies these imbalanced data, is the overlapping instances between the two classes. It is commonly referred to as noise or overlapping data. In this article, we propose an approach called: One Side Behavioral Noise Reduction (OSBNR). This approach presents a way to deal with the problem of class imbalance in the presence of a high noise level. OSBNR is based on two steps. Firstly, a cluster analysis is applied to groups similar instances from the minority class into several behavior clusters. Secondly, we select and eliminate the instances of the majority class, considered as behavioral noise, which overlap with behavior clusters of the minority class. The results of experiments carried out on a representative public dataset confirm that the proposed approach is efficient for the treatment of class imbalances in the presence of noise.

Keywords: machine learning, imbalanced data, data mining, big data

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Authors: Jose Melena, Rosa Santander, Tanya Gonzalez, Richard Duque, Juan Illanes

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Ecuador is one of the countries with the greatest aquatic biodiversity worldwide. In particular, there are at least a dozen native marine species with great aquaculture potential locally. This research concerns one of those species. It has proposed to implement experimental protocols in order to induce spawning and to generate the early larval development of the giant reef clam P. multicostata under controlled conditions. Bioassays were carried out with one adult batch (n= 8) with an average valvar length of 118,4 ± 5,8 mm, which were collected near of the Puerto Santa Rosa (2° 12' 30'' S, 80° 58' 28'' W), Santa Elena Province. During a short acclimation stage, the eight adults of giant reef clam P. multicostata were exposed to thermal stress. Briefly, the experimental protocol for spawning induction was based on the application of 20°C for 1 h and 30°C for 1 h on P. multicostata broodstock at least three consecutive times by one day. After spawning, collected sexual material was released for external fertilization process. After the delivery of gametes, it was achieved 3,25 × 10⁶ viable zygotes. As results, fertilized eggs had 56 µm diameter; while first and second cell divisions were observed to 2,5 h post-fertilization, with individual average length of 68 ± 5 µm and polar body. Latter cell divisions, including gastrula stage, appeared at 9 h post-fertilization, with individual average length of 73 ± 4 µm and trochophore stage at 15 h post-fertilization with individual average length of 75 ± 4 µm. In addition, veliger stage was registered at 20 h post-fertilization with individual average length of 82 ± 6 µm. Umboned larvae appeared at day 8 post-fertilization, with individual average length of 148 ± 6 µm. These pioneering results worldwide can strengthen the local conservation process of the overexploited P. multicostata and to encourage its production for commercial purposes.

Keywords: Ecuador, larval development, Periglypta multicostata, spawning induction

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Authors: Nguyen Cao Nguyen, Krasimir I. Ivanov, Penka S. Zapryanova

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The present study was carried out to investigate the interaction of foliar applied zinc with other elements in Phyllanthus amarus plants. The plant samples for our experiment were collected from Lam Dong province, Vietnam. Seven suspension solutions of nanosized zinc hydroxide nitrate (Zn₅(OH)₈(NO₃)₂·2H₂O) with different Zn concentration were used. Fertilization and irrigation were the same for all variants. The Zn content and the content of selected micro (Cu, Fe, Mn) and macro (Ca, Mg, P and K) nutrients in plant roots, and stems and leaves were determined. It was concluded that the zinc content of plant roots varies narrowly, with no significant impact of ZnHN fertilization. The same trend can be seen in the content of Cu, Mn, and macronutrients. The zinc content of plant stems and leaves varies within wide limits, with the significant impact of ZnHN fertilization. The trends in the content of Cu, Mn, and macronutrients are kept the same as in the root, whereas the iron trends to increase its content at increasing the zinc content.

Keywords: Phyllanthus amarus, Zinc, Micro and macro elements, foliar fertilizer

Procedia PDF Downloads 115

Authors: Maira C. M. Fonseca, Maria Aparecida N. Sediyama, Rosana Goncalves R. das Dores, Sanzio Mollica Vidigal, Alberto C. P. Dias

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Among Brazilian plant diversity, many species are used as food and considered minor crops (non-conventional plant foods) (NCPF). Arrowroot (Maranta arundinacea) is a NCPF from which starch is extracted from rhizome do not have gluten. Thus, arrowroot flower starch can be consumed by celiac people. Additional, some medicinal and functional proprieties are assigned to arrowroot leaves which currently are underutilized. In Brazil, it’s cultivated mainly by small scale farmers and there is no specific recommendation for fertilization. This work aimed to determinate the best fertilization for rhizome production and to verify its influence in phenolic composition and antioxidant activity of leaf extracts. Two arrowroot varieties, “Common” and “Seta”, were cultivated in organic system at state of Minas Gerais, Brazil, using cattle manure with three levels of nitrogen (N) (0, 300 and 900 kg N ha-1). The experiment design was in randomized block with four replicates. The highest production of rhizomes in both varieties, “Common” (38198.24 kg ha-1) and “Seta” (43567.71 kg ha-1), were obtained with the use of 300 kg N ha-1. With this fertilization, the total aerial part, petiole and leaf production in the varieties were respectively: “Common” (190.312 kg ha-1; 159.312 kg ha-1; 31.100 kg ha-1) and “Seta” (207.656 kg ha-1; 180.539 kg ha-1; 27.062 kg ha-1). Methanolic leaf extracts were analysed by HPLC-DAD. The major phenolic compounds found were caffeioylquinic acids, p-coumaric derivatives and flavonoids. In general, the production of these compounds significantly decreases with the increase levels of nitrogen (900 kg N ha-1). With 300 kg N ha-1 the phenolic production was similar to control. The antioxidant activity was evaluated using DPPH method and was detected around 60% of radical scavenging when 0.1 mg/mL of plant extracts were used. We concluded that fertilization with 300 kg N ha-1 increased arrowroot rhizome production, maintaining phenolic compounds yield at leaves.

Keywords: antioxidant activity, non-conventional plants, organic fertilization, phenolic compounds

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Authors: Tais Silva Lopes, Danilo Caneppele, Elizabeth Romagosa

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Surubim-do-Paraíba, Steindachneridion parahybae is a species of South American fish in critical conditions of extinction. Researches have been developed with the objective of conserving the biological material of this species. We evaluated the cooling of mature oocytes in the cryoprotective solutions containing the following alcohols: methanol, Propylene glycol and DMSO, each at concentrations of 1M, 2M and 4M, totaling nine treatments. After being submitted to treatments, the oocytes were maintained for 120 minutes in cooling to -5.52±2.58⁰C. A sample of oocytes was submitted to negative control (NC), kept in 90% L-15 solution, and positive control (PC), fertilized and taken directly to the incubator. Fertilization and hatching rates were evaluated. In order to compare the sensitivity of oocytes to embryos of the same species, the embryos maintained as CP in the previous assay were used in the free-flow stage (about 22 hours post fertilization) and submitted to the same treatments (prepared in distilled water) and also cooled for 120 min. The evaluation was done by the hatch rate. There was no fertilization rate of the oocytes submitted to the cooling with propylene glycol; the other cryoprotectants presented values of at most 3.7% of fertilization (Methanol 1M), and no treatment completed development until hatching. The cooled embryos had a significant percentage of normal larvae in all treatments, but inversely proportional to the increase in the concentration of the alcohols. DMSO 1M was the most promising treatment for embryo cooling, with 41.7% ± 20.2 of normal larvae, while mature oocytes were highly sensitive to cold.

Keywords: cryoconservation, cooling, embryos, freezing, oocytes, south American fish

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Authors: Seungwon Han, Sung young Yoo, Tae Wan Kim

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The objective of this study was to measure the changes in the photochemical response in the leaves of red pepper (Capsium annuum L.) after foliar fertilization of amino acid and small peptides derived from the waste egg. As a nitrogen fertilizer, waste eggs were incubated over one 1week and then degraded as amino acids and small peptides. The smaller peptides less than 20 kDa were identified by matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF-MS). MALDI-TOF-MS as a rapid analysis method was to show the molecular mass of degraded egg protein. The sequences of peptides were identified as follows; γ-Glu- Cys-γ-Glu-Cys-γ-Glu-Cys)-Ser and γ-Glu-Cys-γ-Glu-Cys-γ-Glu- Cys)-Gly. It was clearly illuminated that the parameters related to quantum yields for PSI electron transport (ΦRE1O, ΨRE1O, δRE1O) and RC/ABS have increased tendency by small peptide application. On the other hand, phenomenological energy fluxes (ABSO/CSM, TRO/CSM, ET2O/CSM, RE1O/CSM, DIO/CSM) have considerably fluctuated with foliar fertilization of small peptides. In conclusion, the small peptides can enhance the photochemical activities from photosystem II to photosystem I. This study was financially supported by RDA Agenda Project PJ 016196012022.

Keywords: electron transport, foliar fertilization, small peptide, waste egg

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Authors: Ana Paula Almeida Castaldelli Maciel, Gabriela Medeiros, Amanda de Souza Machado, Maria Clara Pilatti, Ralpho Rinaldo dos Reis, Silvio Cesar Sampaio

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This study evaluates the long-term effects of swine wastewater (SWW) on soil parameters in an agricultural area with years of crop cultivation. Three types of SWW (raw, after leaving the biodigester, and after the manure plant) were analyzed, both with and without mineral fertilization. The study found that the long-term use of SWW had significant effects on soil parameters. Principal Component Analysis (PCA) was used to summarize the data. The soil's calcium (Ca) and magnesium. (Mg), and cation exchange capacity (CEC) levels were higher in soybeans compared to other crops and natural soil. Similarly, the treatment with 0m3.ha-1 of pig manure and without mineral fertilization showed higher levels of these nutrients. In contrast, potassium (K) was found in greater quantities in oats, SWW from the biodigester, higher doses of manure, and mineral fertilization. The crops had a higher organic matter (OM) content compared to the natural soil, with corn and raw SWW showing the most significant increase.

Keywords: contamination, water research, biodigester, nutrients

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Authors: Ghada A. Alfattni

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Analysing unbalanced datasets is one of the challenges that practitioners in machine learning field face. However, many researches have been carried out to determine the effectiveness of the use of the synthetic minority over-sampling technique (SMOTE) to address this issue. The aim of this study was therefore to compare the effectiveness of the SMOTE over different models on unbalanced datasets. Three classification models (Logistic Regression, Support Vector Machine and Nearest Neighbour) were tested with multiple datasets, then the same datasets were oversampled by using SMOTE and applied again to the three models to compare the differences in the performances. Results of experiments show that the highest number of nearest neighbours gives lower values of error rates. 

Keywords: imbalanced datasets, SMOTE, machine learning, logistic regression, support vector machine, nearest neighbour

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Authors: Jose Melena, Rosa Santander, Tanya Gonzalez, Richard Duque, Juan Illanes

Abstract:

Ecuador is one of the countries with the greatest aquatic biodiversity worldwide. In particular, there are at least a dozen native marine species with great aquaculture potential locally. This research concerns one of those species. It has proposed to implement experimental protocols in order to induce spawning and to generate the early larval development of the penshell Atrina maura under controlled conditions. Bioassays were carried out with one adult batch (n= 26) with an average valvar length of 307,6 ± 9,4 mm, which were collected in the Puerto El Morro Mangrove (2° 42' 33'' S, 80° 14' 28'' W), Guayas Province. During a short acclimation stage, five adults of penshell A. maura were sacrificed in order to determine their sexual maturity degree and to estimate their sex ratio. Dissection showed that three were ripe females (60%) and two were ripe males (40%). Later, three groups (n= 7 by each) were tested with two treatments in order to induce the broodstock spawning: thermal stress, osmotic shock, and one control. Spawning induction was achieved by the immersion in water to 0 g L⁻¹ per 1 h and immersion in sea water to 34 g L⁻¹ per 1 h. After the delivery of gametes, it was achieved 1,35 × 10⁶ viable zygotes. As results, fertilized eggs had 60 µm diameter; while first and second cell divisions were observed to 1 h post-fertilization, with individual average length of 65 ± 4 µm and polar body. Latter cell divisions, including gastrula stage, appeared at 9 h post-fertilization, with individual average length of 71 ± 4 µm; and trochophore stage at 16 h post-fertilization with individual average length of 75 ± 5 µm. In addition, veliger stage was registered at 20 h post-fertilization with individual average length of 81 ± 5 µm. Umboned larvae appeared at day 8 post-fertilization, with individual average length of 145 ± 6 µm. These pioneering results in Ecuador can strengthen the local conservation process of the overexploited A. maura and to encourage its production for commercial purposes.

Keywords: Atrina maura, Ecuador, larval development, spawning induction

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Authors: Karla Sanchez-Ortiz, Yunuen Tapia-Torres, John Larsen, Felipe Garcia-Oliva

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Due to food demand production, the use of synthetic nitrogenous fertilizer has increased in agricultural soils to replace the N losses. Nevertheless, the intensive use of synthetic nitrogenous fertilizer in conventional agriculture negatively affects the soil and therefore the environment, so alternatives such as organic agriculture have been proposed for being more environmentally friendly. However, further research in soil is needed to see how agricultural management affects the dynamics of C and N. The objective of this research was to evaluate the C and N dynamics in the soil with three different agricultural management: an agricultural plot with intensive inorganic fertilization, a plot with semi-organic management and an agricultural plot with recent abandonment (2 years). For each plot, the soil C and N dynamics and the enzymatic activity of NAG and β-Glucosidase were characterized. Total C and N concentration of the plant biomass of each site was measured as well. Dissolved organic carbon (DOC) and dissolved organic nitrogen (DON) was higher in abandoned plot, as well as this plot had higher total carbon (TC) and total nitrogen (TN), besides microbial N and microbial C. While the enzymatic activity of NAG and β-Glucosidase was greater in the agricultural plot with inorganic fertilization, as well as nitrate (NO₃) was higher in fertilized plot, in comparison with the other two plots. The aboveground biomass (AB) of maize in the plot with inorganic fertilization presented higher TC and TN concentrations than the maize AB growing in the semiorganic plot, but the C:N ratio was highest in the grass AB in the abandoned plot. The C:N ration in the maize grain was greater in the semi-organic agricultural plot. These results show that the plot under intensive agricultural management favors the loss of soil organic matter and N, degrading the dynamics of soil organic compounds, promoting its fertility depletion.

Keywords: mineralization, nitrogen cycle, soil degradation, soil nutrients

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Authors: Ahsan Abdullah, Ahmed A. S. Bakshwain

Abstract:

Livestock is one of the fastest-growing sectors in agriculture. If carefully managed, have potential opportunities for economic growth, food sovereignty and food security. In this study we mainly analyse and compare long-term i.e. for year 2030 climate variability impact on predicted productivity of meat i.e. beef, mutton and poultry for the Kingdom of Saudi Arabia w.r.t three factors i.e. i) climatic-change vulnerability ii) CO2 fertilization and iii) water scarcity and compare the results with two countries of the region i.e. Iraq and Yemen. We do the analysis using data from diverse sources, which was extracted, transformed and integrated before usage. The collective impact of the three factors had an overall negative effect on the production of meat for all the three countries, with adverse impact on Iraq. High similarity was found between CO2 fertilization (effecting animal fodder) and water scarcity i.e. higher than that between production of beef and mutton for the three countries considered. Overall, the three factors do not seem to be favorable for the three Middle-East countries considered. This points to possibility of a vegetarian year 2030 based on dependency on indigenous live-stock population.

Keywords: prediction, animal-source foods, pastures, CO2 fertilization, climatic-change vulnerability, water scarcity

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Authors: Doyin Afolabi, Phillip Adewole, Oladipupo Sennaike

Abstract:

Most well-known classifiers, including the decision tree algorithm, can make predictions on balanced datasets efficiently. However, the decision tree algorithm tends to be biased towards imbalanced datasets because of the skewness of the distribution of such datasets. To overcome this problem, this study proposes a weighted decision tree algorithm that aims to remove the bias toward the majority class and prevents the reduction of majority observations in imbalance datasets classification. The proposed weighted decision tree algorithm was tested on three imbalanced datasets- cancer dataset, german credit dataset, and banknote dataset. The specificity, sensitivity, and accuracy metrics were used to evaluate the performance of the proposed decision tree algorithm on the datasets. The evaluation results show that for some of the weights of our proposed decision tree, the specificity, sensitivity, and accuracy metrics gave better results compared to that of the ID3 decision tree and decision tree induced with minority entropy for all three datasets.

Keywords: data mining, decision tree, classification, imbalance dataset

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Authors: Babak Qasemi-Panahi, Gholamali Moghaddam, Seyed-Abbas Rafat, Hossein Daghigh Kia, Mansoureh Movahedin, Reza Hadavi

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The objective of this study was to determine the effects of IGF-I on ovine oocytes maturation and subsequent development of embryos derived from in vitro fertilization (IVF). In vitro maturation (IVM) of oocytes and in vitro culture (IVC) of embryos was conducted with or without 100 ng/mL IGF-1. In the IGF-I treated group, mean percentage of oocyte maturation was significantly higher than the control group (57.67 ± 3.04 versus 49.81 ± 3.04%, respectively, P < 0.05). However, in comparison with control group, there was no significant effect of IGF-1 on rates of cleavage, morula, and blastocyst formation (85% versus 84%; 63% versus 65%, and 40% to 39%, respectively). These data demonstrate that IGF-I has a positive effect on ovine oocyte maturation rate, but it has not the significant outcome on embryo development.

Keywords: ovine, IGF-I, IVM, ICSI

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Authors: Krasimir Ivanov, Tonyo Tonev, Nguyen Nguyen, Alexander Peltekov, Anyo Mitkov

Abstract:

Maize is among the most economically important crops and at the same time one of the most sensitive to soil deficiency in zinc. In this paper, the impact of the foliar zinc application in the form of zinc hydroxy nitrate suspension on the micro and macro elements partitioning in maize leaves and grain was studied during spring maize season, 2017. The impact of the foliar zinc fertilization on the grain yield and quality was estimated too. The experiment was performed by the randomized block design with 8 variants in 3 replications. Seven suspension solutions whit different Zn concentration were used, including ZnO suspension and zinc hydroxyl nitrate alone or nixed with other nutrients. Fertilization and irrigation were the same for all variants. The Zn content and the content of selected micro (Cu, Fe) and macro (Ca, Mg, P and K) elements in maize leaves were determined two weeks after the first spraying (5-6 sheets), two weeks after the second spraying (9-10 sheets) and after harvesting. It was concluded that the synthesized zinc hydroxy nitrate demonstrates potential as the long-term foliar fertilizer. A significant (p < 0.05) effect of zinc accumulation in maize leaves by foliar zinc application during the first growth stage was found, followed by its reutilization to other plants organs during the second growth stage. Significant export of Cu, P, and K from lower and middle leaves was observed. The content of Ca and Mg remains constant in the whole longevity period, while the content of Fe decreases sharply.

Keywords: foliar fertilization, zinc hydroxy nitrate, maize, zinc

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Authors: Anita Kushwaha

Abstract:

We propose a new evolutionary computational model called Artificial Reproduction System which is based on the complex process of meiotic reproduction occurring between male and female cells of the living organisms. Artificial Reproduction System is an attempt towards a new computational intelligence approach inspired by the theoretical reproduction mechanism, observed reproduction functions, principles and mechanisms. A reproductive organism is programmed by genes and can be viewed as an automaton, mapping and reducing so as to create copies of those genes in its off springs. In Artificial Reproduction System, the binding mechanism between male and female cells is studied, parameters are chosen and a network is constructed also a feedback system for self regularization is established. The model then applies Mendel’s law of inheritance, allele-allele associations and can be used to perform data analysis of imbalanced data, multivariate, multiclass and big data. In the experimental study Artificial Reproduction System is compared with other state of the art classifiers like SVM, Radial Basis Function, neural networks, K-Nearest Neighbor for some benchmark datasets and comparison results indicates a good performance.

Keywords: bio-inspired computation, nature- inspired computation, natural computing, data mining

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Authors: Eun Jeong Yu, Inn Soo Kang, Tae Ki Yoon, Mi Kyoung Koong

Abstract:

Advanced female age is associated with higher cycle cancelation rates, lower clinical pregnancy rate, increased miscarriage and aneuploidy rates in IVF (In Vitro Fertilization) cycles. This retrospective cohort study was conducted at a Cha Fertility Center, Seoul Station. All fresh non-donor IVF cycles performed in women aged 40 years and above from January 2016 to December 2016 were reviewed. Donor/recipient treatment, PGD/PGS (Preimplantation Genetic Diagnosis/ Preimplantation Genetic Screening) were excluded from analysis. Of the 1,166 cycles from 753 women who completed ovulation induction, 1,047 were appropriate for the evaluation according to inclusion and exclusion criterion. IVF cycles were categorized according to age and grouped into the following 1-year age groups: 40, 41, 42, 43, 44, 45 and > 46. The mean age of patients was 42.4 ± 1.8 years. The median AMH (Anti-Mullerian Hormone) level was 1.2 ± 1.5 ng/mL. The mean number of retrieved oocytes was 4.9 ± 4.3. The clinical pregnancy rate and live birth rate in women > 40 years significantly decreased with each year of advancing age (p < 0.001). The clinical pregnancy rate decreased from 21% at the age of 40 years to 0% at ages above 45 years. Live birth rate decreased from 12.3% to 0%, respectively. There were no clinical pregnancy outcomes among 95 patients aged above 45 years of age. The overall miscarriage rate was 40.7% (range, 36.7%-70%). The transfer of at least one good quality embryo was associated with about 4-9% increased chance of a clinical pregnancy rate. Therefore, IVF in old age women less than 46 had a reasonable chance for successful pregnancy outcomes especially when good quality embryo is transferred.

Keywords: advanced maternal age, in vitro fertilization, pregnancy rate, live birth rate

Procedia PDF Downloads 117