Search results for: tomato yield prediction

Authors: Omar Ibrahim, Aly A. Gaafar, K. A. Ratib

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Two field experiments in micro plots were carried out during the winter seasons of 2012/2013 and 2013/2014, Soil Salinity Laboratory, Alexandria, Egypt, to study the effect of three levels of salicylic acid (SA) as a growth regulator (0, 50, 100 ppm) and three rates of nitrogen fertilizer (75, 100, 125 kg N/feddan) on growth and yield of a spring wheat (Giza 168). The experimental design was a split plot with the main plots in randomized complete block design (RCBD) and four replicates. The results indicated that increasing nitrogen fertilizer rates resulted in insignificant effect on both plant height (cm) and grain weight/spike only. However, a significant effect was observed in all the other studied characters due to the increase in nitrogen fertilizer. On the other hand, increasing salicylic acid rates resulted in insignificant effect in all the studied characters except for chlorophyll a, chlorophyll b, number of grain/spike, and grain yield (gm/ plot). The highest effects on grain yield in wheat were obtained by the rate of 125 kg/feddan of nitrogen fertilizer and 100 ppm of salicylic acid. In conclusion, the data indicated that a high grain yield could be obtained by adding 100 kg/feddan of nitrogen fertilizer and spraying of 50 ppm of salicylic acid with no significant difference with the highest rates. Finally, the interaction had no significant effect on all the studied characters.

Keywords: growth regulator, nitrogen fertilizer, spring wheat, salicylic acid

Procedia PDF Downloads 117

Authors: Omvati Verma, Shyamashrre Roy

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A field experiment was conducted with three basal nitrogen levels (90, 120 and 150 kg N/ha) and five foliar application of urea (absolute control, water spray, 3% urea spray at anthesis, 7 and 14 days after anthesis) at G.B. Pant University of Agriculture & Technology, Pantnagar, U.S. Nagar (Uttarakhand) during rabi season in a factorial randomized block design with three replications. Results revealed that nitrogen application of 150 kg/ha produced the highest seed yield, straw and biological yield and it was significantly superior to 90 kg N/ha and was at par with 120 kg N/ha. The number of tillers increased significantly with increase in nitrogen doses up to 150 kg N/ha. Spike length, number of grains per spike, grain weight per spike and thousand seed weight showed significantly higher values with 120 kg N/ha than 90 kg N/ha and were at par with that of 150 kg N/ha. Also, plant height showed similar trend. Leaf area index and chlorophyll content showed significant increase with an increase in nitrogen levels at different stages. In the case of foliar spray treatments, urea spray at anthesis showed highest value for yield and yield attributes. In case of spike length and thousand seed weight, it was similar with the urea spray at 7 and 14 days after anthesis, but for rest of the yield attributes, it was significantly higher than rest of the treatments. Among seed quality parameters protein and sedimentation value showed significant increase due to increase in nitrogen rates whereas, starch and hectolitre weight had a decreasing trend. Wet gluten content was not influenced by nitrogen levels. Foliar urea spray at anthesis resulted in highest value of protein and hectolitre weight whereas, urea spray at 7 days after anthesis showed highest value of sedimentation value and wet gluten content.

Keywords: foliar application, nitrogenous fertilizer, seed quality, yield

Procedia PDF Downloads 279

Authors: D. I. George Amalarethinam, A. Emima

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Educational Data Mining (EDM) is one of the newest topics to emerge in recent years, and it is concerned with developing methods for analyzing various types of data gathered from the educational circle. EDM methods and techniques with machine learning algorithms are used to extract meaningful and usable information from huge databases. For scientists and researchers, realistic applications of Machine Learning in the EDM sectors offer new frontiers and present new problems. One of the most important research areas in EDM is predicting student success. The prediction algorithms and techniques must be developed to forecast students' performance, which aids the tutor, institution to boost the level of student’s performance. This paper examines various classification techniques in prediction methods and data mining tools used in EDM.

Keywords: classification technique, data mining, EDM methods, prediction methods

Procedia PDF Downloads 115

Authors: Osung Im, Neha Yadav, Eui Hoon Lee, Joong Hoon Kim

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Artificial Neural Network (ANN) approach is commonly used in lots of fields for forecasting. In water resources engineering, forecast of water level or inflow of reservoir is useful for various kind of purposes. Due to advantages of ANN, many papers were written for inflow prediction in river networks, but in this study, ANN is used in urban sewer networks. The growth of severe rain storm in Korea has increased flood damage severely, and the precipitation distribution is getting more erratic. Therefore, effective pump operation in pump station is an essential task for the reduction in urban area. If real time inflow of pump station reservoir can be predicted, it is possible to operate pump effectively for reducing the flood damage. This study used ANN model for pump station reservoir inflow prediction using upstream sewer depth data. For this study, rainfall events, sewer depth, and inflow into Banpo pump station reservoir between years of 2013-2014 were considered. Feed – Forward Back Propagation (FFBF), Cascade – Forward Back Propagation (CFBP), Elman Back Propagation (EBP) and Nonlinear Autoregressive Exogenous (NARX) were used as ANN model for prediction. A comparison of results with ANN model suggests that ANN is a powerful tool for inflow prediction using the sewer depth data.

Keywords: artificial neural network, forecasting, reservoir inflow, sewer depth

Procedia PDF Downloads 317

Authors: Chanunya Fahwan, Supat Chaiyakul

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A lactose-free diet is imperative for those with lactose intolerance and experiencing milk intolerance. This entails eliminating milk-based products, which may result in dietary and nutritional challenges and the main problems of Lactose hydrolyzed milk powder during production were the adhesion in the drying chamber and low-yield and low-quality powder. The use of lactose-free milk to produce lactose-free milk powder was studied here. Development of two milk powder formulas from cow's milk and lactose-free cow's milk by using a substitute for maltodextrin, Polydextrose (PDX), Resistant Starch (RS), Cellobiose (CB), and Resistant Maltodextrin (RMD) to improve quality and reduce the glycemic index from maltodextrin, which are carriers that were used in industry at three experimental levels 10%, 15% and 20% the properties of milk powder were studied such as color, moisture content, percentage yield (%yield) and solubility index. The experiment revealed that prebiotic carriers could replace maltodextrin and improve quality, such as solubility and percentage yield, and enriched nutrients, such as dietary fiber. CB, RMD, and PDX are three possible carriers, which are applied to both regular cow's milk formula and lactose-free cow milk.

Keywords: lactose-free milk powder, prebiotic carrier, co-particle, glycemic index

Procedia PDF Downloads 81

Authors: Ayat E. Ali, Christeen R. Aziz, Merna A. Helmy, Mohammed M. Malek, Sherif H. El-Gohary

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Goal: Purpose of the project was to make a plastic surgery prediction by using pre-operative images for the plastic surgeries’ patients and to show this prediction on a screen to compare between the current case and the appearance after the surgery. Methods: To this aim, we implemented a software which used data from the internet for facial skin diseases, skin burns, pre-and post-images for plastic surgeries then the post- surgical prediction is done by using K-nearest neighbor (KNN). So we designed and fabricated a smart mirror divided into two parts a screen and a reflective mirror so patient's pre- and post-appearance will be showed at the same time. Results: We worked on some skin diseases like vitiligo, skin burns and wrinkles. We classified the three degrees of burns using KNN classifier with accuracy 60%. We also succeeded in segmenting the area of vitiligo. Our future work will include working on more skin diseases, classify them and give a prediction for the look after the surgery. Also we will go deeper into facial deformities and plastic surgeries like nose reshaping and face slim down. Conclusion: Our project will give a prediction relates strongly to the real look after surgery and decrease different diagnoses among doctors. Significance: The mirror may have broad societal appeal as it will make the distance between patient's satisfaction and the medical standards smaller.

Keywords: k-nearest neighbor (knn), face detection, vitiligo, bone deformity

Procedia PDF Downloads 163

Authors: Isaac Mugume, Charles Basalirwa, Daniel Waiswa, Triphonia Ngailo

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Rainfall is a major climatic parameter affecting many sectors such as health, agriculture and water resources. Its quantitative prediction remains a challenge to weather forecasters although numerical weather prediction models are increasingly being used for rainfall prediction. The performance of six convective parameterization schemes, namely the Kain-Fritsch scheme, the Betts-Miller-Janjic scheme, the Grell-Deveny scheme, the Grell-3D scheme, the Grell-Fretas scheme, the New Tiedke scheme of the weather research and forecast (WRF) model regarding quantitative rainfall prediction over Uganda is investigated using the root mean square error for the March-May (MAM) 2013 season. The MAM 2013 seasonal rainfall amount ranged from 200 mm to 900 mm over Uganda with northern region receiving comparatively lower rainfall amount (200–500 mm); western Uganda (270–550 mm); eastern Uganda (400–900 mm) and the lake Victoria basin (400–650 mm). A spatial variation in simulated rainfall amount by different convective parameterization schemes was noted with the Kain-Fritsch scheme over estimating the rainfall amount over northern Uganda (300–750 mm) but also presented comparable rainfall amounts over the eastern Uganda (400–900 mm). The Betts-Miller-Janjic, the Grell-Deveny, and the Grell-3D underestimated the rainfall amount over most parts of the country especially the eastern region (300–600 mm). The Grell-Fretas captured rainfall amount over the northern region (250–450 mm) but also underestimated rainfall over the lake Victoria Basin (150–300 mm) while the New Tiedke generally underestimated rainfall amount over many areas of Uganda. For deterministic rainfall prediction, the Grell-Fretas is recommended for rainfall prediction over northern Uganda while the Kain-Fritsch scheme is recommended over eastern region.

Keywords: convective parameterization schemes, March-May 2013 rainfall season, spatial variation of parameterization schemes over Uganda, WRF model

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Authors: Angeliki Peponi, Paulo Morgado, Jorge Trindade

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Artificial Neural Networks (ANNs) and Geographic Information Systems (GIS) are applied as a robust tool for modeling and forecasting the erosion changes in Costa Caparica, Lisbon, Portugal, for 2021. ANNs present noteworthy advantages compared with other methods used for prediction and decision making in urban coastal areas. Multilayer perceptron type of ANNs was used. Sensitivity analysis was conducted on natural and social forces and dynamic relations in the dune-beach system of the study area. Variations in network’s parameters were performed in order to select the optimum topology of the network. The developed methodology appears fitted to reality; however further steps would make it better suited.

Keywords: artificial neural networks, backpropagation, coastal urban zones, erosion prediction

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Authors: Yen-Hui Chen, Terry Walker

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As the world experiences an energy crisis, investing in sustainable energy resources is a pressing mission for many countries. Microalgae-derived biodiesel has attracted intensive attention as an important biofuel, and microalgae Chlorella protothecoides lipid is recognized as a renewable source for microalgae-derived biodiesel production. Supercritical carbon dioxide (SC-CO₂) is a promising green solvent that may potentially substitute the use of organic solvents for lipid extraction; however, the efficiency of SC-CO₂ extraction may be affected by many variables, including temperature, pressure and extraction time individually or in combination. In this study, response surface methodology (RSM) was used to optimize the process parameters, including temperature, pressure and extraction time, on C. protothecoides lipid yield by SC-CO₂ extraction. A second order polynomial model provided a good fit (R-square value of 0.94) for the C. protothecoides lipid yield. The linear and quadratic terms of temperature, pressure and extraction time—as well as the interaction between temperature and pressure—showed significant effects on lipid yield during extraction. The optimal lipid yield from the model was predicted as the temperature of 59 °C, the pressure of 350.7 bar and the extraction time 2.8 hours. Under these conditions, the experimental lipid yield (25%) was close to the predicted value. The principal fatty acid methyl esters (FAME) of C. protothecoides lipid-derived biodiesel were oleic acid methyl ester (60.1%), linoleic acid methyl ester (18.6%) and palmitic acid methyl ester (11.4%), which made up more than 90% of the total FAMEs. In summary, this study indicated that RSM was useful to characterize the optimization the SC-CO₂ extraction process of C. protothecoides lipid yield, and the second-order polynomial model could be used for predicting and describing the lipid yield very well. In addition, C. protothecoides lipid, extracted by SC-CO₂, was suggested as a potential candidate for microalgae-derived biodiesel production.

Keywords: Chlorella protothecoides, microalgal lipids, response surface methodology, supercritical carbon dioxide extraction

Procedia PDF Downloads 443

Authors: S. B. Kalaghatagi, A. K. Guggari, Pallavi S. Manikashetti

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A field experiment to study the effect of band application of organic manures on growth and yield of pigeon pea was conducted during 2016-17 at Kharif Seed Farm, College of Agriculture, Vijayapura. The experiment was carried out in randomized block design with thirteen treatments viz., T1 to T6 were band application of vermicompost at 0.5, 1.0, 1.5, 2.0, 2.5, 3.0 t ha⁻¹, respectively. The treatments T7 to T12 include band application of sieved FYM at 1, 2, 3, 4, 5 and 6 t ha⁻¹, respectively and were compared with already recommended practice of broadcasting of FYM at 6 t ha⁻¹ (T13); and recommended dose of fertilizer (25:50:0 NPK kg ha⁻¹) was applied commonly to all the treatments. The results revealed that band application of vermicompost (VC) at 3 t ha⁻¹ recorded significantly higher number of pods plant⁻¹ (116), grain weight plant⁻¹ (37.35 g), grain yield (1,647 kg ha⁻¹), stalk yield (2,920 kg ha⁻¹) and harvest index (0.36) and was on par with the band application of VC at 2.0 and 2.5 t ha⁻¹ and sieved FYM at 4.0 and 5.0 t ha⁻¹ as compared to broadcasting of FYM at 6 t ha-1 (99.33, 24.07 g, 1,061 kg ha⁻¹, 2,920 kg ha⁻¹ and 0.36, respectively). Significantly higher net return (Rupees 59,410 ha⁻¹) and benefit cost ratio of 2.92 recorded with band application of VC at 3 t ha⁻¹ over broadcasting of FYM at 6 tonnes per ha (Rupees 25,401 ha⁻¹ and 1.78, respectively). It indicates from the above results that, growing of pigeon pea with band application of VC at 2, 2.5 and 3 t ha⁻¹ and sieved FYM at 4 and 5 t ha⁻¹ leads to saving of 1 tonne of VC and 2 tonnes of FYM per ha.

Keywords: organic manures, rainfed pigeonpea, sieved FYM, vermicompost

Procedia PDF Downloads 212

Authors: Selvaprakash Ramalingam, Rabi N. Sahoo, Dharmendra Saraswat, A. Kumar, Rajeev Ranjan, Joydeep Mukerjee, Viswanathan Chinnasamy, K. K. Chaturvedi, Sanjeev Kumar

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Rice is one of the most important staple food crops in the world. Among the various diseases that affect rice crops, rice blast is particularly significant, causing crop yield and economic losses. While the plant has defense mechanisms in place, such as chemical indicators (proteins, salicylic acid, jasmonic acid, ethylene, and azelaic acid) and resistance genes in certain varieties that can protect against diseases, susceptible varieties remain vulnerable to these fungal diseases. Early prediction of rice blast (RB) disease is crucial, but conventional techniques for early prediction are time-consuming and labor-intensive. Hyperspectral remote sensing techniques hold the potential to predict RB disease at its asymptomatic stage. In this study, we aimed to demonstrate the prediction of RB disease at the asymptomatic stage using non-imaging hyperspectral ASD spectroradiometer under controlled laboratory conditions. We applied statistical spectral discrimination theory to identify unknown spectra of M. Oryzae, the fungus responsible for rice blast disease. The infrared (IR) region was found to be significantly affected by RB disease. These changes may result in alterations in the absorption, reflection, or emission of infrared radiation by the affected plant tissues. Our research revealed that the protein spectrum in the IR region is impacted by RB disease. In our study, we identified strong correlations in the region (Amide group - I) around X 1064 nm and Y 1300 nm with the Lambda / Lambda derived spectra methods for protein detection. During the stages when the disease is developing, typically from day 3 to day 5, the plant's defense mechanisms are not as effective. This is especially true for the PB-1 variety of rice, which is highly susceptible to rice blast disease. Consequently, the proteins in the plant are adversely affected during this critical time. The spectral contour plot reveals the highly correlated spectral regions 1064 nm and Y 1300 nm associated with RB disease infection. Based on these spectral sensitivities, we developed new spectral disease indices for predicting different stages of disease emergence. The goal of this research is to lay the foundation for future UAV and satellite-based studies aimed at long-term monitoring of RB disease.

Keywords: rice blast, asymptomatic stage, spectral sensitivity, IR

Procedia PDF Downloads 86

Authors: B. B. Rana, M. Yokota, Y. Shimizu, Y. Koide, I. Takamure, T. Kawano, M. Murai

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Various genes which control or affect heading time have been found in rice. Out of them, Se1 and E1 loci play important roles in determining heading time by controlling photosensitivity. An isogenic-line pair of late and early lines were developed from progenies of the F₁ from Suweon 258 × 36U. A lateness gene tentatively designated as “Ex” was found to control the difference in heading time between the early and late lines mentioned above. The present study was conducted to examine the effect of Ex on yield and related traits. Indica-type variety Suweon 258 was crossed with 36U, which is an Ur1 (Undulate rachis-1) isogenic line of IR36. In the F₂ population, comparatively early-heading, late-heading and intermediate-heading plants were segregated. Segregation similar to that by the three types of heading was observed in the F₃ and later generations. A late-heading plant and an early-heading plant were selected in the F₈ population from an intermediate-heading F₇ plant, for developing L and E of the isogenic-line pair, respectively. Experiments for L and E were conducted by randomized block design with three replications. Transplanting was conducted on May 3 at a planting distance of 30 cm × 15 cm with two seedlings per hill to an experimental field of the Faculty of Agriculture, Kochi University. Chemical fertilizers containing N, P₂O₅ and K₂O were applied at the nitrogen levels of 4 g/m², 9 g/m² and 18 g/m² in total being denoted by "N4", "N9" and "N18", respectively. Yield, yield components and other traits were measured. Ex delayed 80%-heading by 17 or 18 days in L as compared with E. In total brown rice yield (g/m²), L was 635, 606 and 590, and E was 577, 548 and 501, respectively, at N18, N9 and N4, indicating that Ex increased this trait by 10% to 18%. Ex increased yield-1.5 mm sieve (g/m²) b 9% to 15% at the three fertilizer levels. Ex increased the spikelet number per panicle by 16% to 22%. As a result, the spikelet number per m² was increased by 11% to 18% at the three fertilizer levels. Ex decreased 1000-grain weight (g) by 2 to 4%. L was not significantly different from E in ripened-grain percentage, fertilized-spikelet percentage and percentage of ripened grains to fertilized spikelets. Hence, it is inferred that Ex increased yield by increasing spikelet number per panicle. Hence, Ex could be utilized to develop high yielding varieties for warmer districts.

Keywords: heading time, lateness gene, photosensitivity, yield, yield components

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Authors: Sumit Sen, Sohan Khedekar, Umang Shinde, Shivam Bhargava

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This study has been undertaken to investigate whether the deep learning models are able to predict the future stock prices by training the model with the historical stock price data. Since this work required time series analysis, various models are present today to perform time series analysis such as Recurrent Neural Network LSTM, ARIMA and Facebook Prophet. Applying these models the movement of stock price of stocks are predicted and also tried to provide the future prediction of the stock price of a stock. Final product will be a stock price prediction web application that is developed for providing the user the ease of analysis of the stocks and will also provide the predicted stock price for the next seven days.

Keywords: Autoregressive Integrated Moving Average, Deep Learning, Long Short Term Memory, Time-series

Procedia PDF Downloads 141

Authors: Falodun E. J., Ogbeifun S. O.

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The objectives of this study were to investigate the yield, nutrient concentration, and uptake of fluted pumpkin (Telfairia occidentalis Hook. f.) in response to spacing and fertilizer application. Two fluted pumpkin plant populations (10,000 and 20,000 plants ha⁻¹), D1 and D2, were evaluated at three levels of NPK fertilizer (F₁, 20 t ha⁻¹ poultry manure, F₂, 300 kg ha⁻¹ NPK 15:15:15 and F₃, 10 t ha⁻¹ poultry manure + 150 kg ha⁻¹ NPK 15:15:15) using a factorial arrangement in a randomized complete block design (RCBD) with three replications. Leaf length, breadth, and the number of leaves were significantly increased at a lower plant population of 10,000 plants ha⁻¹ while herbage yield increased with a higher plant population of 20,000 plants ha⁻¹ using 300 kg ha⁻¹ inorganic NPK 15:15:15 or a combination of 10 t ha⁻¹ poultry manure + 150 kg ha⁻¹ inorganic NPK 15:15:15. Potassium (K) concentration was significantly (p < 0.05) higher at 10,000 plants ha⁻¹ and Iron (Fe) uptake was higher with combine application of organic and inorganic fertilizer (F3). To maximize the good herbage yield of fluted pumpkins, farmers in this locality should adopt a plant population of 20,000 plants ha⁻¹ using 300 kg ha⁻¹ inorganic NPK 15:15:15 (D2F2) or a combination of 10 t ha⁻¹ poultry manure + 150 kg ha⁻¹ inorganic NPK 15:15:15 (D2F3).

Keywords: fertilizers, fluted pumpkin, herbage yield, plant population

Procedia PDF Downloads 188

Authors: E. Tarantino, G. Disciglio, G. Gatta, L. Frabboni, A. Libutti, A. Tarantino

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Worldwide, about two-thirds of industrial and domestic wastewater effluent is discharged without treatment, which can cause contamination and eutrophication of the water. In particular, for Mediterranean countries, irrigation with treated wastewater would mitigate the water stress and support the agricultural sector. Changing global weather patterns will make the situation worse, due to increased susceptibility to drought, which can cause major environmental, social, and economic problems. The study was carried out in open field in an intensive agricultural area of the Apulian region in Southern Italy where freshwater resources are often scarce. As well as providing a water resource, irrigation with treated wastewater represents a significant source of nutrients for soil–plant systems. However, the use of wastewater might have further effects on soil. This study thus investigated the long-term impact of irrigation with reclaimed agro-industrial wastewater on the chemical characteristics of the soil. Two crops (processing tomato and broccoli) were cultivated in succession in Stornarella (Foggia) over four years from 2012 to 2016 using two types of irrigation water: groundwater and tertiary treated agro-industrial wastewater that had undergone an activated sludge process, sedimentation filtration, and UV radiation. Chemical analyses were performed on the irrigation waters and soil samples. The treated wastewater was characterised by high levels of several chemical parameters including TSS, EC, COD, BOD₅, Na⁺, Ca²⁺, Mg²⁺, NH₄-N, PO₄-P, K⁺, SAR and CaCO₃, as compared with the groundwater. However, despite these higher levels, the mean content of several chemical parameters in the soil did not show relevant differences between the irrigation treatments, in terms of the chemical features of the soil.

Keywords: agro-industrial wastewater, broccoli, long-term re-use, tomato

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Authors: Adel M. Mahmoud

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This Investigation was conducted to determine the productivity and water use efficiency for new sunflower genotypes. Ten sunflower genotypes were evaluated under drip irrigation using two treatments of. Results indicate that decreasing the amount of irrigation water from 1500 to 1130 mm/hectar significantly reduced all studied traits. Mutation (M1-63) surpassed all the other one genotypes in seed yield and WUE. Lines which gave the highest yield of the seed have water use efficiency under drought conditions higher than water use efficiency under normal irrigation. The lowest depression in seed yield due to drought conditions has been registered for Line 20, Line M1-63 and Sakha 53 genotypes (11 , 18 and 16 %, respectively). Genotypes (Line 20 , Line M1-63 and Sakha 53) are more tolerant to drought than others and we can used its in breeding program to develop sunflower hybrids suitable for cultivation under drought condition.

Keywords: sunflower genotypes, water use efficiency, mutation, inbred lines

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Authors: Salman Mohamadi, Seyed Mohammad Ali Tayaranian Hosseini, Hamidreza Amindavar

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In this paper, we provide a procedure to analyze and model EEG (electroencephalogram) signal as a time series using ARIMA-GARCH to predict an epileptic attack. The heteroskedasticity of EEG signal is examined through the ARCH or GARCH, (Autore- gressive conditional heteroskedasticity, Generalized autoregressive conditional heteroskedasticity) test. The best ARIMA-GARCH model in AIC sense is utilized to measure the volatility of the EEG from epileptic canine subjects, to forecast the future values of EEG. ARIMA-only model can perform prediction, but the ARCH or GARCH model acting on the residuals of ARIMA attains a con- siderable improved forecast horizon. First, we estimate the best ARIMA model, then different orders of ARCH and GARCH modelings are surveyed to determine the best heteroskedastic model of the residuals of the mentioned ARIMA. Using the simulated conditional variance of selected ARCH or GARCH model, we suggest the procedure to predict the oncoming seizures. The results indicate that GARCH modeling determines the dynamic changes of variance well before the onset of seizure. It can be inferred that the prediction capability comes from the ability of the combined ARIMA-GARCH modeling to cover the heteroskedastic nature of EEG signal changes.

Keywords: epileptic seizure prediction , ARIMA, ARCH and GARCH modeling, heteroskedasticity, EEG

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Authors: B. S. Chandrashekar, M. K. Prasannakumar, P. Buela Parivallal, Sahana N. Banakar, Swathi S. Patil, H. B. Mahesh, D. Pramesh

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Bacterial soft rot is one of the most often seen diseases in many plant species globally, resulting in considerable yield loss. Radish roots with dark water-soaked lesions, maceration of tissue, and a foul odour were collected in the Kolar region, India. Two isolates were obtained from rotted samples that demonstrated morphologically unpigmented, white mucoid convex colonies on nutrient agar medium. The isolated bacteria (RDH1 and RDH3) were gram-negative, rod-shaped bacteria with biochemically distinct characteristics similar to the type culture of Enterobacter cloacae ATCC13047 and Bergy's handbook of determinative bacteriology. The 16s rRNA gene was used to identify Enterobacter species. On carrot, potato, tomato, chilli, bell pepper, knolkhol, cauliflower, cabbage, and cucumber slices, the Koch′s postulates were fulfilled, and the pathogen was also pathogenic on radish, cauliflower, and cabbage seedlings were grown in a glasshouse. After 36 hours, both isolates exhibited a hypersensitive sensitivity to Nicotianatabacum. Semi-quantitative analysis revealed that cell wall degrading enzymes (CWDEs) such as pectin lyase, polygalacturonase, and cellulase (p=1.4e09) contributed to pathogenicity, whereas isolates produced biofilms (p=4.3e-11) that help in host adhesion. This is the first report in India of radish soft rot caused by E. cloacae.

Keywords: soft rot, enterobacter cloacae, 16S rRNA, nicotiana tabacum, and pathogenicity

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Authors: Rahim Ada, Ahmet Tamkoç

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The research was conducted in the “Randomized Complete Block Design” with three replications in research field of Agricultural Faculty, Selcuk University, Konya, Turkey. In study, a total of 9 Cephalaria syriaca promised lines (9, 37, 38, 42, Beyaz 4, 5 Beyaz, 13 Beyaz, 27 Beyaz, Başaklar 2), which were taken from Sivas population, and 1 population were evaluated in two growing seasons (2012-13 and 2013-14). According to the results, the highest plant height, first branch height, first head height, number of branches per plant, number of head per plant, head diameter,1000 seed weight, seed yield, oil content and oil yield were obtained respectively from Başaklar 2 (68.37 cm), Başaklar 2 (37.80 cm), Başaklar 2 (54.83 cm), 37 (7.73 number/plant), 42 (18.03 number/plant), 9 (10.30 mm), Başaklar 2 (19.33 g), 27 Beyaz (1254.2 kg ha-1), Başaklar 2 (28.77%), and 27 Beyaz (357.9 kg ha-1).

Keywords: Cephalaria syriaca, yield, oil, population

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Authors: Javed Sidiqi, Stephen Baezinger, Stephen Wegulo

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Wheat (Triticum aestivum L.) production continues to be challenged by foliar fungal diseases although significant improvement has been made to manage the diseases through developing resistant varieties and the fungicide use to ensure sufficient wheat is produced to meet the growing population’s need. Significant crop losses have been recorded in the history of grain production and yield losses due to fungal diseases, and the trend continues to threat food security in the world and particularly in the less developed countries. The impact of individual fungal diseases on grain yield has been studied extensively to determine crop losses. However, there is limited research available to find out the combined effects of fungal diseases on grain yield and the ways to effectively manage the diseases. Therefore, the objectives of this research were to study the effect of fungal pathogens on grain yield of pre-released winter wheat genotypes in fungicide treated and untreated plots, and to determine whether S7b gene was present in ‘Gage’ wheat as previously hypothesized. Sixty winter wheat genotypes in fungicide treated and untreated plots were studied across four environments. There was a significant effect of fungicide on grain yield consistently across four environments in three years. Fungicide treated wheat lines demonstrated (4,496 kg/ ha-1) grain yield compared to (3,147 kg/ ha-1) grain yield in untreated wheat lines indicating 43% increased grain yield due to severity of foliar fungal diseases. Furthermore, fungicide application also caused an increase in protein concentration from 153 (g kg-1) to 164 (g kg-1) in treated plots in along with test weight from 73 to 77 (kg hL-1) respectively. Gage wheat variety and ISr7b-Ra were crossed to determine presence of Sr7b in Gage. The F2 and F2:3 segregating families were screened and evaluated for stem rust resistance. The segregation of families fell within 15:1 ratio for two separate resistance genes suggesting that Sr7b segregates independently from an unknown resistance gene in Gage that needs to be characterized for its use in the future wheat breeding program to develop resistant wheat varieties.

Keywords: funicide, genetics, foliar diseases, grain

Procedia PDF Downloads 126

Authors: Darshan Panda, Lambodar Behera, M. J. Baig, Sudhanshu Sekhar

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Low light intensity is a significant limitation for grain yield and quality in rice. However, yield is not significantly reduced in low-light tolerant rice varieties. The work, therefore, planned for comparative transcriptome profiling under low light stress to decipher the genes involved and molecular mechanism of low light tolerance in rice. At the active tillering stage, 50% low light exposure for one day, three days, and five days were given to Swarnaprabha (low light tolerant) and IR8 (low light sensitive) rice varieties. Illumina (HiSeq) platform was used for transcriptome sequencing. A total of 6,652 and 12,042 genes were differentially expressed due to low light intensity in Swarnaprabha and IR8, respectively, as compared to control. CAB, LRP, SBPase, MT15, TF PCL1, and Photosystem I & II complex related gene expressions were mostly increased in Swarnaprabha upon the longer duration of low light exposure, which was not found in IR8 as compared to control. Their expressions were validated by qRT-PCR. The overall study suggested that the maintenance of grain yield in the tolerant variety under low light might be the result of accelerated expression of the genes, which enable the plant to keep the photosynthetic processes moving at the same pace even under low light.

Keywords: rice, low light, photosynthesis, yield

Procedia PDF Downloads 194

Authors: Masoud Rafiee

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To study the quality response of forage to chickpea-barley mixed cropping under drought stress and vermicompost consumption, an experiment was carried out under well watered and %70 water requirement (stress condition) in RCBD as split plot with four replications in temperate condition of Khorramabad in 2013. Chickpea-barley mix cropping (%100 chickpea, %75:25 chickpea:barley, %50:50 chickpea:barley, %25:75 chickpea:barley, and %100 barley) was studied. Results showed that wet and dry forage yield were significantly affected by environment and decreased in stress condition. Also, crude protein content decreased from %26.2 in well watered to %17.3 in stress condition.

Keywords: crude protein, wet forage yield, dry forage yield, water stress condition, well watered

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Authors: Arun K. Yadav, Adam J. Carroll, Gonzalo M. Estavillo, Greg J. Rebetzke, Barry J. Pogson

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Water limits crop productivity, so selecting for minimal yield-gap in drier environments is critical to mitigate against climate change and land-use pressures. To date, no markers measured in glasshouses have been reported to predict field-based drought tolerance. In the field, the best measure of drought tolerance is yield-gap; but this requires multisite trials that are an order of magnitude more resource intensive and can be impacted by weather variation. We investigated the responses of relative water content (RWC), stomatal conductance (gs), chlorophyll content and metabolites in flag leaves of commercial wheat (Triticum aestivum L.) cultivars to three drought treatments in the glasshouse and field environments. We observed strong genetic associations between glasshouse-based RWC, metabolites and Yield gap-based Drought Tolerance (YDT): the ratio of yield in water-limited versus well-watered conditions across 24 field environments spanning sites and seasons. Critically, RWC response to glasshouse drought was strongly associated with both YDT (r2 = 0.85, p < 8E-6) and RWC under field drought (r2 = 0.77, p < 0.05). Multiple regression analyses revealed that 98% of genetic YDT variance was explained by drought responses of four metabolites: serine, asparagine, methionine and lysine (R2 = 0.98; p < 0.01). Fitted coefficients suggested that, for given levels of serine and asparagine, stronger methionine and lysine accumulation was associated with higher YDT. Collectively, our results demonstrate that high-throughput, targeted metabolic phenotyping of glasshouse-grown plants may be an effective tool for the selection of wheat cultivars with high YDT in the field.

Keywords: drought stress, grain yield, metabolomics, stomatal conductance, wheat

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Authors: Kisan Sarda, Bhavika Shingote

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This paper aims to evaluate regression modelling for prediction of Energy storage of solar photovoltaic (PV) system using Semi parametric regression techniques because there are some parameters which are known while there are some unknown parameters like humidity, dust etc. Here irradiation of solar energy is different for different places on the basis of Latitudes, so by finding out areas which give more storage we can implement PV systems at those places and our need of energy will be fulfilled. This regression modelling is done for daily, monthly and seasonal prediction of solar energy storage. In this, we have used R modules for designing the algorithm. This algorithm will give the best comparative results than other regression models for the solar PV cell energy storage.

Keywords: semi parametric regression, photovoltaic (PV) system, regression modelling, irradiation

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Authors: Mohammad Saeri, Zainal Arifin

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The purpose of this study is to obtain information on technical and social-economic feasibility of sugarcane-soybean. To achieve these objectives, soybeans intercropping study was conducted in sugar cane crops. This assessment was conducted in two locations with different agroecosystem,ie lowland of low plain in Mojokerto, East Java, with altitude of 50m above sea level and upland of medium plain in Malang, East Javawithaltitude of 500 m above the sea level. The design used was Split plot, with the main plots, is the soybean varieties, consisting of: (a) Anjasmoro, (b) Argomulyo, and (c) Dena-1, while the subplot is bio-fertilizer, consisting of : (1) Agrimeth, (2) Agrisoy, and (3) Biovarm. The variables observed were growth, yield and yield components and economic analysis. The yield of soybean in lowland reached 0.74 t/ha of seeds with farm profit of Indonesian Rupiah 359.200. This result is relatively low due to the delay of soybean cultivation from sugar cane soup time so that sugar cane cover soybean cultivation, while in upland obtained 0.92t/ha seeds with farm profit of Indonesian Rupiah 2,015,000. Therefore, it is suggested that soybeans are planted immediately after ratoon cane so that soybean growth can be optimal before the growth of sugarcane cover the soil surface. The yield of sugar cane in the lowland reached 124.5 tons with a profit of Indonesian Rupiah. 21,200,000,- while in upland obtained by sugarcane yield equal to 78,5 ton with profit equal to Indonesian Rupiah 8,900,000,-.

Keywords: intercropping, sugar cane, soybean, profit, farming

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Authors: Prabir Kumar Paul, Joyeeta Mitra

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Ergosterol, is an important fungal metabolite on phylloplane which is not synthesised by plants. However, the functional requirement of ergosterol to the plants is still an enigma. Being ubiquitously present in all plants except algae needs an insight into its physiological implication. The present study aimed at understanding if and how ergosterol influences the physiology of chloroplast particularly the activity of RuBisCo and carbonic anhydrase. The concept of the study was based on one of our earlier observation of enhanced Hills reaction in plants treated with fungal metabolites which contained ergosterol. The fungal metabolite treated plants had a significantly high concentration of photosynthetic pigments. Eight-week-old tomato plants raised under aseptic conditions at 25 + 10 C, 75 % relative humidity and 12 hour L/D photoperiod. Metabolites of Aspergillus niger and Fusarium oxysporum were sprayed on plants either singly or in a 1: 1 combination. A separate group of plants was also treated with 0.5, 1.0, 3.0, 5.0. 7.0 mg ergosterol / ml of n- heptane. Control plants were treated with sterile distilled water only. Plants were sampled at 24, 48, 72 and 96 hours of treatment. RuBisCo and carbonic anhydrase was estimated from sampled leaves. RuBisCo was separated on 1D SDS-PAGE and subjected to MALDI – TOF- TOF – MS analysis. The presence of ergosterol in fungal metabolites was confirmed. Fungal metabolites significantly enhanced the concentration and activity of RuBisCo and carbonic anhydrase. The Vmax activity of the enzymes was significantly high in metabolite treated plants. 1:1 mix of metabolite was more effective than when applied individually. Insilico analysis revealed, RuBisCo subunits had a binding site for ergosterol and in its presence affinity of Co2 to the enzyme increased by several folds. Invivo activity of RuBisCo was significantly elicited by ergosterol. Results of the present study indicate that ergosterol from phylloplane microfungi probably regulates the binding of Co2 to RuBisCo along with activity of carbonic anhydrase thereby modulating the physiology of choloroplast.

Keywords: carbonic anhydrase, ergosterol, phylloplane, RuBisCo

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Authors: Amira Racha Ben Yakoub, Ali Ferchichi

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In order to investigate the impact of sowing time on growth parameters, the length of the development cycle and yield of tossa jute (Corchorus olitorius L.), a field experiment was conducted from March to May 2011 at the Laboratoire d’Aridoculture et Cultures Oasiennes, ‘Institut des Régions Arides de Médénine’, Tunisia. Results of the experiment revealed that the early sowing (the middle of March, the beginning of April) induced a cycle of more than 100 days to reach the stage maturity and generates a marked drop in production. This period of plantation affects plant development and leads to a sharp drop in performance marked primarily by a reduction in growth, number and size of leaves, number of flowers and pods and weight of different parts of plant. Sowing from the end of April seems appropriate for shortening the development cycle and better profitability than the first two dates. Seeding of C. olitorius during May enhance the development of plants more dense, which explains the superiority of production marked by the increase of seed yield and leaf fresh and dry weight of this leafy vegetables.

Keywords: tossa jute (Corchorus olitorius L), sowing date, growth, yield

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Authors: Anita Singh, Richa Naula, Manoj Raghav

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India is a leading producer and consumer of fenugreek for its culinary uses and medicinal application. In India, most of the people are of vegetarian class. In such a situation, a leafy vegetable, such as fenugreek is of chief concern due to its high nutritional property, medicinal values and industrial uses. One of the most important factors restricting their large scale production and development of superior varieties is that very scanty knowledge about their genetic diversity, inter and intraspecific variability and genetic relationship among the species. Improvement of the crop depends upon the magnitude of genetic variability for economic characters. Therefore, the present research work was carried out to analyse the variability parameters for growth and yield character in twenty-eight fenugreek genotypes along with two standard checks Pant Ragini and Pusa Early Bunching. The experiment was laid out in Randomized Block Design with three replication during rabi season 2015-2016 at Pantnagar Centre for Plant Genetic Resources, G.B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand. The analysis of variance revealed highly significant differences among all the genotypes for all traits. High genotypic and phenotypic coefficient variation were observed for characters, namely the number of primary branches per plant, number of leaves at 30, 45 and 60 DAS, green leaf yield per plant, green leaf yield q/ha . The genetic advance recorded highest in green leaf yield q/ha (33.93) followed by green leaf yield per plant (21.20g). Highest percent of heritability were shown by 1000 seed weight (99.12%) followed by the number of primary branches per plant (97.18%). Green leaf yield q/ha showed high heritability and high genetic advance. These superior genotypes can be further used in crop improvement programs of fenugreek.

Keywords: genetic advance, genotypic coefficient variation, heritability, phenotypic coefficient variation

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Authors: Mohammad Taghi Karbalaei Aghamolki, Mohd Khanif Yusop, Fateh Chand Oad, Hamed Zakikhani, Hawa Zee Jaafar, Sharifh Kharidah, Mohamed Hanafi Musa, Shahram Soltani

Abstract:

The high temperatures during sensitive growth phases are changing rice morphology as well as influencing yield. In the glass house study, the treatments were: growing conditions [normal growing (32oC+2) and heat stress (38oC+2) day time and 22oC+2 night time], growth stages (booting, flowering and ripening) and four cultivars (Hovaze, Hashemi, Fajr, as exotic and MR219 as indigenous). The heat chamber was prepared covered with plastic, and automatic heater was adjusted at 38oC+2 (day) and 22oC+2 (night) for two weeks in every growth stages. Rice morphological and yield under the influence of heat stress during various growth stages showed taller plants in Hashsemi due to its tall character. The total tillers per hill were significantly higher in Fajr receiving heat stress during booting stage. In all growing conditions and growth stages, Hashemi recorded higher panicle exertion and flag leaf length. The flag leaf width in all situations was found higher in Hovaze. The total tillers per hill were more in Fajr, although heat stress was imposed during booting and flowering stages. The indigenous MR219 in all situations of growing conditions, growth stages recorded higher grain yield. However, its grain yield slightly decreased when heat stress was imposed during booting and flowering. Similar results were found in all other exotic cultivars recording to lower grain yield in the heat stress condition during booting and flowering. However, plants had no effect on heat stress during ripening stage.

Keywords: rice, growth, heat, temperature, stress, morphology, yield

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Authors: Jingling Li, Yi Zhang, Wei Liang, Tao Cui, Jun Li

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Compared with terrestrial network, the traffic of spatial information network has both self-similarity and short correlation characteristics. By studying its traffic prediction method, the resource utilization of spatial information network can be improved, and the method can provide an important basis for traffic planning of a spatial information network. In this paper, considering the accuracy and complexity of the algorithm, the spatial information network traffic is decomposed into approximate component with long correlation and detail component with short correlation, and a time series hybrid prediction model based on wavelet decomposition is proposed to predict the spatial network traffic. Firstly, the original traffic data are decomposed to approximate components and detail components by using wavelet decomposition algorithm. According to the autocorrelation and partial correlation smearing and truncation characteristics of each component, the corresponding model (AR/MA/ARMA) of each detail component can be directly established, while the type of approximate component modeling can be established by ARIMA model after smoothing. Finally, the prediction results of the multiple models are fitted to obtain the prediction results of the original data. The method not only considers the self-similarity of a spatial information network, but also takes into account the short correlation caused by network burst information, which is verified by using the measured data of a certain back bone network released by the MAWI working group in 2018. Compared with the typical time series model, the predicted data of hybrid model is closer to the real traffic data and has a smaller relative root means square error, which is more suitable for a spatial information network.

Keywords: spatial information network, traffic prediction, wavelet decomposition, time series model

Procedia PDF Downloads 146