Search results for: crop models

Authors: Meng-Fei Cheng, Wei Fneg

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New Taiwan high school standards emphasize employing scientific models and modeling practices in physics learning. However, to our knowledge. Few studies address how scientific models and modeling are approached in current science teaching, and they do not examine the views of scientific models portrayed in the textbooks. To explore the views of scientific models and modeling in textbooks, this study investigated the atomic unit in different textbook versions as an example and provided suggestions for modeling curriculum. This study adopted a quantitative analysis of qualitative data in the atomic units of four mainstream version of Taiwan high school physics textbooks. The models were further analyzed using five dimensions of the views of scientific models (nature of models, multiple models, purpose of the models, testing models, and changing models); each dimension had three levels (low, medium, high). Descriptive statistics were employed to compare the frequency of describing the five dimensions of the views of scientific models in the atomic unit to understand the emphasis of the views and to compare the frequency of the eight scientific models’ use to investigate the atomic model that was used most often in the textbooks. Descriptive statistics were further utilized to investigate the average levels of the five dimensions of the views of scientific models to examine whether the textbooks views were close to the scientific view. The average level of the five dimensions of the eight atomic models were also compared to examine whether the views of the eight atomic models were close to the scientific views. The results revealed the following three major findings from the atomic unit. (1) Among the five dimensions of the views of scientific models, the most portrayed dimension was the 'purpose of models,' and the least portrayed dimension was 'multiple models.' The most diverse view was the 'purpose of models,' and the most sophisticated scientific view was the 'nature of models.' The least sophisticated scientific view was 'multiple models.' (2) Among the eight atomic models, the most mentioned model was the atomic nucleus model, and the least mentioned model was the three states of matter. (3) Among the correlations between the five dimensions, the dimension of 'testing models' was highly related to the dimension of 'changing models.' In short, this study examined the views of scientific models based on the atomic units of physics textbooks to identify the emphasized and disregarded views in the textbooks. The findings suggest how future textbooks and curriculum can provide a thorough view of scientific models to enhance students' model-based learning.

Keywords: atomic models, textbooks, science education, scientific model

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Authors: Azar Khodabakhshi, Elham Bolandnazar

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Agriculture as the most important food manufacturing sector is not only the energy consumer, but also is known as energy supplier. Using energy is considered as a helpful parameter for analyzing and evaluating the agricultural sustainability. In this study, the pattern of energy consumption of strawberry greenhouses of Jiroft in Kerman province of Iran was surveyed. The total input energy required in the strawberries production was calculated as 113314.71 MJ /ha. Electricity with 38.34% contribution of the total energy was considered as the most energy consumer in strawberry production. In this study, Neuro Fuzzy networks was used for function modeling in the production of strawberries. Results showed that the best model for predicting the strawberries function had a correlation coefficient, root mean square error (RMSE) and mean absolute percentage error (MAPE) equal to 0.9849, 0.0154 kg/ha and 0.11% respectively. Regards to these results, it can be said that Neuro Fuzzy method can be well predicted and modeled the strawberry crop function.

Keywords: crop yield, energy, neuro-fuzzy method, strawberry

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Authors: Suprehatin Suprehatin

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Improving the participation of smallholder farmers in horticultural value chains to benefit from the rapidly growing demand for high-value agricultural products is one strategy for raising farm income. However, smallholder farmer participation in Indonesian horticultural value chains is under-researched. To address this knowledge gap, this study aims to describe the current status of horticultural crop adoption in Indonesia and analyze the motivations and dynamics of smallholder farmer participation in horticultural value chains: why some small farmers join these new and potentially profitable chains and continue their participation. This study also examines the characteristics of farmers who adopted and those who did not adopt a new horticultural crop with respect to the household (farmer), farm and institutional characteristics. The analysis was conducted using unique data from a 2013 survey of 960 Indonesian farmers on Java Island that produce a variety of agricultural products. Basic statistical analysis showed relatively low adoption rates (10%) of new horticultural crops amongst 960 selected Indonesian farmers with different decisions made in terms of number and timing of new horticultural crop adoption. Adopters were motivated mainly by higher profit, higher yield, and more cash opportunities. The result also showed that current low rates of horticultural crop adoption are associated with a variety of factors, such as lower levels of education among farmers, resource constraints, lack of information on horticultural crop production and low participation in farmer groups. These findings will be helpful for policymakers when designing policies and programs to promote greater participation of Indonesian smallholder farmers in horticultural value chains. In other words, a revitalisation of agricultural policy beyond staple food is important to seize potential benefits from the ongoing agricultural food market transformation.

Keywords: farmer adoption, high value, horticultural crops, Indonesia

Procedia PDF Downloads 251

Authors: G. Disciglio, G. Gatta, F. Lops, A. Libutti, A. Tarantino, E. Tarantino

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The experimental trial was carried out in open field at Foggia district (Apulia Region, Southern Italy), during the spring-summer season 2014, in order to evaluate the effect of four biostimulant products (RadiconÒ, Viormon plusÒ, LysodinÒ and SiaptonÒ 10L), compared with a control (no biostimulant), on the infestation of processing tomato crop (cv Dres) by the chlorophyll-lacking root parasite Phelipanche ramosa. Biostimulants consist in different categories of products (microbial inoculants, humic and fulvic acids, hydrolyzed proteins and aminoacids, seaweed extracts) which play various roles in plant growing, including the improvement of crop resistance and quali-quantitative characteristics of yield. The experimental trial was arranged according to a complete randomized block design with five treatments, each of one replicated three times. The processing tomato seedlings were transplanted on 5 May 2014. Throughout the crop cycle, P. ramosa infestation was assessed according to the number of emerged shoots (branched plants) counted in each plot, at 66, 78 and 92 day after transplanting. The tomato fruits were harvested at full-stage of maturity on 8 August 2014. From each plot, the marketable yield was measured and the quali-quantitative yield parameters (mean weight, dry matter content, colour coordinate, colour index and soluble solids content of the fruits) were determined. The whole dataset was tested according to the basic assumptions for the analysis of variance (ANOVA) and the differences between the means were determined using Tukey’s tests at the 5% probability level. The results of the study showed that none of the applied biostimulants provided a whole control of Phelipanche, although some positive effects were obtained from their application. To this respect, the RadiconÒ appeared to be the most effective in reducing the infestation of this root-parasite in tomato crop. This treatment also gave the higher tomato yield.

Keywords: biostimulant, control methods, Phelipanche ramosa, tomato crop

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Authors: Valdir Moura, Raniele dos Anjos de Souza, Fernando Gomes de Souza, Jose Vagner da Silva, Jerry Adriani Johann

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The estimate of the Area of Land to be planted with annual crops and its stratification by the municipality are important variables in crop forecast. Nowadays in Brazil, these information’s are obtained by the Brazilian Institute of Geography and Statistics (IBGE) and published under the report Assessment of the Agricultural Production. Due to the high cloud cover in the main crop growing season (October to March) it is difficult to acquire good orbital images. Thus, one alternative is to work with remote sensing data from dates before the crop growing season. This work presents the use of multitemporal Landsat data gathered on July and September (before the summer growing season) in order to estimate the area of land to be planted with summer crops in an area of São Paulo State, Brazil. Geographic Information Systems (GIS) and digital image processing techniques were applied for the treatment of the available data. Supervised and non-supervised classifications were used for data in digital number and reflectance formats and the multitemporal Normalized Difference Vegetation Index (NDVI) images. The objective was to discriminate the tracts with higher probability to become planted with summer crops. Classification accuracies were evaluated using a sampling system developed basically for this study region. The estimated areas were corrected using the error matrix derived from these evaluations. The classification techniques presented an excellent level according to the kappa index. The proportion of crops stratified by municipalities was derived by a field work during the crop growing season. These proportion coefficients were applied onto the area of land to be planted with summer crops (derived from Landsat data). Thus, it was possible to derive the area of each summer crop by the municipality. The discrepancies between official statistics and our results were attributed to the sampling and the stratification procedures. Nevertheless, this methodology can be improved in order to provide good crop area estimates using remote sensing data, despite the cloud cover during the growing season.

Keywords: area intended for summer culture, estimated area planted, agriculture, Landsat, planting schedule

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Authors: Kedibone Masenya, Memory Tekere, Jasper Rees

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Sorghum is an important cereal crop in the world. In particular, it has attracted breeders due to capacity to serve as food, feed, fiber and bioenergy crop. Like any other plant, sorghum hosts a variety of microbes, which can either, have a neutral, negative and positive influence on the plant. In the current study, regions (V3/V4) of 16 S rRNA were targeted to extensively assess bacterial multitrophic interactions in the phyllosphere of sorghum. The results demonstrated that the presence of a pathogen has a significant effect on the endophytic bacterial community. Understanding these interactions is key to develop new strategies for plant protection.

Keywords: bacteria, multitrophic, sorghum, target sequencing

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Authors: Abdelghafour Galadi

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In this paper, accurate power MOSFET models including quasi-saturation effect are presented. These models have no internal node voltages determined by the circuit simulator and use one JFET or one depletion mode MOSFET transistors controlled by an “effective” gate voltage taking into account the quasi-saturation effect. The proposed models achieve accurate simulation results with an average error percentage less than 9%, which is an improvement of 21 percentage points compared to the commonly used standard power MOSFET model. In addition, the models can be integrated in any available commercial circuit simulators by using their analytical equations. A description of the models will be provided along with the parameter extraction procedure.

Keywords: power MOSFET, drift layer, quasi-saturation effect, SPICE model

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Authors: Ayman Aboelkassem, Mohamoud Ali, Rezq Diab

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This project aims to document and preserve boat models which were discovered in the Saqqara by Czech Institute of Egyptology archeological mission at Saqqara (GEM numbers, 46007, 46008, 46009). These boat models dates back to Egyptian Old Kingdom and have been transferred to the Conservation Center of the Grand Egyptian Museum, to be displayed at the new museum.The project objectives making such boat models more visible to visitors through the use of 3D reconstructed models and high resolution photos which describe the history of using the boats during the Ancient Egyptian history. Especially, The Grand Egyptian Museum is going to exhibit the second boat of King Khufu from Old kingdom. The project goals are to document the boat models and arrange an exhibition, where such Models going to be displayed next to the Khufu Second Boat. The project shows the importance of using boats in Ancient Egypt, and connecting their usage through Ancient Egyptian periods till now. The boat models had a unique Symbolized in ancient Egypt and connect the public with their kings. The Egyptian kings allowed high ranked employees to put boat models in their tombs which has a great meaning that they hope to fellow their kings in the journey of the afterlife.

Keywords: archaeology, boat models, 3D digital tools for heritage management, museums

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Authors: Suparman

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Piecewise linear regression models are very flexible models for modeling the data. If the piecewise linear regression models are matched against the data, then the parameters are generally not known. This paper studies the problem of parameter estimation of piecewise linear regression models. The method used to estimate the parameters of picewise linear regression models is Bayesian method. But the Bayes estimator can not be found analytically. To overcome these problems, the reversible jump MCMC algorithm is proposed. Reversible jump MCMC algorithm generates the Markov chain converges to the limit distribution of the posterior distribution of the parameters of picewise linear regression models. The resulting Markov chain is used to calculate the Bayes estimator for the parameters of picewise linear regression models.

Keywords: regression, piecewise, Bayesian, reversible Jump MCMC

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Authors: Amer Ait Sidhoum

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Interest in sustainability has gained ground among practitioners, academics and policy-makers due to growing stakeholders’ awareness of environmental and social concerns. This is particularly true for agriculture. However, relatively little research has been conducted on the quantification of social sustainability and the contribution of social issues to the agricultural production efficiency. This research's main objective is to propose a method for evaluating prices of social outputs, more precisely shadow prices, by allowing for the stochastic nature of agricultural production that is to say for production uncertainty. In this article, the assessment of social outputs’ shadow prices is conducted within the methodological framework of nonparametric Data Envelopment Analysis (DEA). An output-oriented directional distance function (DDF) is implemented to represent the technology of a sample of Catalan arable crop farms and derive the efficiency scores the overall production technology of our sample is assumed to be the intersection of two different sub-technologies. The first sub-technology models the production of random desirable agricultural outputs, while the second sub-technology reflects the social outcomes from agricultural activities. Once a nonparametric production technology has been represented, the DDF primal approach can be used for efficiency measurement, while shadow prices are drawn from the dual representation of the DDF. Computing shadow prices is a method to assign an economic value to non-marketed social outcomes. Our research uses cross sectional, farm-level data collected in 2015 from a sample of 180 Catalan arable crop farms specialized in the production of cereals, oilseeds and protein (COP) crops. Our results suggest that our sample farms show high performance scores, from 85% for the bad state of nature to 88% for the normal and ideal crop growing conditions. This suggests that farm performance is increasing with an improvement in crop growth conditions. Results also show that average shadow prices of desirable state-contingent output and social outcomes for efficient and inefficient farms are positive, suggesting that the production of desirable marketable outputs and of non-marketable outputs makes a positive contribution to the farm production efficiency. Results also indicate that social outputs’ shadow prices are contingent upon the growing conditions. The shadow prices follow an upward trend as crop-growing conditions improve. This finding suggests that these efficient farms prefer to allocate more resources in the production of desirable outputs than of social outcomes. To our knowledge, this study represents the first attempt to compute shadow prices of social outcomes while accounting for the stochastic nature of the production technology. Our findings suggest that the decision-making process of the efficient farms in dealing with social issues are stochastic and strongly dependent on the growth conditions. This implies that policy-makers should adjust their instruments according to the stochastic environmental conditions. An optimal redistribution of rural development support, by increasing the public payment with the improvement in crop growth conditions, would likely enhance the effectiveness of public policies.

Keywords: data envelopment analysis, shadow prices, social sustainability, sustainable farming

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Authors: Ali Bolat, Ali Bayat, Mustafa Gullu

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Maize can be cultivated both under main and second crop conditions in Turkey. Main pests of maize under second crop conditions are Sesamia nonagrioides Lefebvre (Lepidoptera: Noctuidae) and Ostrinia nubilalis Hübner (Lepidoptera: Crambidae). Aerial spraying applications to control these two main maize pests can be carried out until 2006 in Turkey before it was banned due to environmental concerns like drifting of sprayed pestisides and low biological efficiency. In this context, pulverizers which can spray tall maize plants ( > 175 cm) from the ground have begun to be used. However, the biological efficiency of these sprayers is unknown. Some methods have been tested to increase the success of ground spraying in field experiments conducted in second crop maize in 2008 and 2009. For this aim, 6 spraying methods (air assisted spraying with TX cone jet, domestic cone nozzles, twinjet nozzles, air induction nozzles, standard domestic cone nozzles and tail booms) were used at two application rates (150 and 300 l.ha-1) by a sprayer. In the study, biological efficacy evaluations of each methods were measured in each parcel. Biological efficacy evaluations included counts of number of insect damaged plants, number of holes in stems and live larvae and pupa in stems of selected plants. As a result, the highest biological efficacy value (close to 70%) was obtained from Air Assisted Spraying method at 300 l / ha application volume.

Keywords: air assisted sprayer, drift nozzles, biological efficiency, maize plant

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Authors: Mehdi Rostamzadeh

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Genetic Algorithms (GAs) are an adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetic. In this study, we apply GAs for fundamental and technical models of exchange rate determination in exchange rate market. In this framework, we estimated absolute and relative purchasing power parity, Mundell-Fleming, sticky and flexible prices (monetary models), equilibrium exchange rate and portfolio balance model as fundamental models and Auto Regressive (AR), Moving Average (MA), Auto-Regressive with Moving Average (ARMA) and Mean Reversion (MR) as technical models for Iranian Rial against European Union’s Euro using monthly data from January 1992 to December 2014. Then, we put these models into the genetic algorithm system for measuring their optimal weight for each model. These optimal weights have been measured according to four criteria i.e. R-Squared (R2), mean square error (MSE), mean absolute percentage error (MAPE) and root mean square error (RMSE).Based on obtained Results, it seems that for explaining of Iranian Rial against EU Euro exchange rate behavior, fundamental models are better than technical models.

Keywords: exchange rate, genetic algorithm, fundamental models, technical models

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Authors: Fatih Tarlak

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Predictive microbiology can be considered as an important field in food microbiology in which it uses predictive models to describe the microbial growth in different food products. Predictive models estimate the growth of microorganisms quickly, efficiently, and in a cost-effective way as compared to traditional methods of enumeration, which are long-lasting, expensive, and time-consuming. The mathematical models used in predictive microbiology are mainly categorised as primary and secondary models. The primary models are the mathematical equations that define the growth data as a function of time under a constant environmental condition. The secondary models describe the effects of environmental factors, such as temperature, pH, and water activity (aw) on the parameters of the primary models, including the maximum specific growth rate and lag phase duration, which are the most critical growth kinetic parameters. The combination of primary and secondary models provides valuable information to set limits for the quantitative detection of the microbial spoilage and assess product shelf-life.

Keywords: shelf-life, growth model, predictive microbiology, simulation

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Authors: Pascal François Faye, Baye Mor Sall, Bineta Dembele, Jeanne Ana Awa Faye

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In agriculture, estimating crop yields is key to improving productivity and decision-making processes such as financial market forecasting and addressing food security issues. The main objective of this paper is to have tools to predict and improve the accuracy of crop yield forecasts using machine learning (ML) algorithms such as CART , KNN and SVM . We developed a mobile app and a web app that uses these algorithms for practical use by farmers. The tests show that our system (collection and deployment architecture, web application and mobile application) is operational and validates empirical knowledge on agro-climatic parameters in addition to proactive decision-making support. The experimental results obtained on the agricultural data, the performance of the ML algorithms are compared using cross-validation in order to identify the most effective ones following the agricultural data. The proposed applications demonstrate that the proposed approach is effective in predicting crop yields and provides timely and accurate responses to farmers for decision support.

Keywords: prediction, machine learning, artificial intelligence, digital agriculture

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Authors: Rabin Paudel, Dambar Bahadur Mahato, Prabin Poudel, Bijaya Neupane, Sakar Jha

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Understanding Human-Elephant Conflict (HEC) is very important in countries like Nepal, where solutions to escalating conflicts are urgently required. However, most of the HEC mitigation measures implemented so far have been done on an ad hoc basis without the detailed understanding of nature and extent of the damage. This study aims to assess the current scenario of HEC in regards to crop and property damages by Wild Asian Elephant and people’s perception towards existing mitigating measures and elephant conservation in Buffer zone area of Bardia National Park. The methods used were a questionnaire survey (N= 178), key-informant interview (N= 18) and focal group discussions (N= 6). Descriptive statistics were used to determine the nature and extent of damage and to understand people’s perception towards HEC, its mitigation measures and elephant conservation. Chi-square test was applied to determine the significance of crop and property damages with respect to distance from the park boundary. Out of all types of damage, crop damage was found to be the highest (51%), followed by house damage (31%) and damage to stored grains (18%) with winter being the season with the greatest elephant damage. Among 178 respondents, the majority of them (82%) were positive towards elephant conservation despite the increment in HEC incidents as perceived by 88% of total respondents. Among the mitigation measures present, the most applied was electric fence (91%) followed by barbed wire fence (5%), reinforced concrete cement wall (3%) and gabion wall (1%). Most effective mitigation measures were reinforced concrete cement wall and gabion wall. To combat increasing crop damage, the insurance policy should be initiated. The efficiency of the mitigation measures should be timely monitored, and corrective measures should be applied as per the need.

Keywords: crop and property damage, elephant conflict, Asiatic wild elephant, mitigation measures

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Authors: Cosmas Parwada, Ronald Mandumbu, Handseni Tibugari, Trust Chinyama

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A 3-yr field experiment to evaluate effects of tillage and residue management on soil water storage (SWS), grain yield, harvest index (HI) and water use efficiency (WUE) of sorghum was done in sandy soils. Treatments were conventional (CT) and minimum (MT) tillage without residue retention and conventional (CT × RT) and minimum (MT × RT) tillage with residue retention. Change in SWS was higher under CT and MT than in CT × RT and MT × RT, especially in the 0-10 cm soil layer. Grain yield and HI were significantly (P < 0.05) lower in CT and MT than CT × RT and MT × RT. Grain yield and HI were significantly (P < 0.05) positively correlated to WUE but WUE significantly (P < 0.05) negatively correlated to sand (%) particle content. The SWS was lower in winter but higher in summer and was significantly correlated to soil organic carbon (SOC), sand (%), grain yield (t/ha), HI and WUE. The WUE linearly increasing from first to last cropping seasons in tillage with returned residues; higher in CT × RT and MT × RT that promoted SOC buildup than where crop residues were removed. Soil tillage decreased effects of residues on SWS, WUE, grain yield and HI. Minimum tillage coupled to residue retention sustainably enhanced WUE but further research to investigate the interaction effects of the tillage on WUE and soil fertility management is required. Understanding and considering the WUE in crops can be a primary condition for cropping system designs. The findings pave way for further research and crop management programmes, allowing to valorize the water in crop production.

Keywords: evapotranspiration, infiltration rate, organic mulch, sand, water use efficiency

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Authors: Xuewen Chen, Aizhen Liang, Xiaoping Zhang

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To better understand the spatial variability of soil penetration resistance (SPR) and soil water content (SWC) induced by different tillage and crop rotation in a Mollisol of Northeast China, the soil was sampled from the tillage experiment which was established in Dehui County, Jilin Province, Northeast China, in 2001. Effect of no-tillage (NT), moldboard plow (MP) and ridge tillage (RT) under corn-soybean rotation (C-S) and continuous corn (C-C) system on SPR and SWC were compared with horizontal and vertical variations. The results showed that SPR and SWC spatially varied across the ridge. SPR in the rows was higher than inter-rows, especially in topsoil (2.5-15 cm) of NT and RT plots. SPR of MP changed in the trend with the curve-shaped ridge. In contrast to MP, NT, and RT resulted in average increment of 166.3% and 152.3% at a depth of 2.5-17.5 cm in the row positions, respectively. The mean SPR in topsoil in the rows means soil compaction is not the main factor limiting plant growth and crop yield. SPR in the row of RT soil was lower than NT at a depth of 2.5-12.5 cm. The SWC in NT and RT soil was highest in the inter-rows and least in the rows or shoulders, respectively. However, the lateral variation trend of MP was opposite to NT. From the profile view of SWC, MP was greater than NT and RT in 0-20 cm of the rows. SWC in RT soil was higher than NT in the row of 0-20 cm. Crop rotation did not have a marked impact on SPR and SWC. In addition to the tillage practices, the factor which affects SPR greatly was depth but not position. These two factors have significant effects on SWC. These results indicated that the adoption of RT was a more suitable conservation tillage practices than NT in the black soil of Northeast China.

Keywords: row, soil penetration resistance, spatial variability, tillage practice

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Authors: Meysam Abedinpour

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Water limitation is the main challenge for crop production in a semi-arid environment. Deficit irrigation is a strategy that allows a crop to sustain some degree of water deficit in order to reduce costs and potentially increase income. For this goal, a field experimental carried out at Asrieh fields of Gorgan city in the north of Iran, during summer season 2011. The treatments imposed were different irrigation water regimes (i.e. W1:70, W2:80, W3:90, and W4:100) percent of field capacity (FC). The results showed that there was Significant difference between the yield and (WUE) under different levels of irrigation, excepting of soil moisture content at field capacity (W4) and 90% of field capacity (W3) on yield and water use efficiency (WUE). The seasonal irrigation water applied were (i.e. 375, 338, 300, and 263 mm ha-1) under different irrigation water treatments (100, 90, 80, 80 and 70%) of FC, respectively. Grain yield productions under treatments were 4180, 3955, 3640, and 3355 (kg ha-1) respectively. Furthermore, the results showed that water use efficiency (WUE) at different treatments were 7.67, 7.79, 7.74, and 7.75 Kg mm ha-1 for (100, 90, 80, and 70) per cent of field capacity, therefore the 90 % of FC treatment (W3) is recommended for Soybean irrigation for water saving. Furthermore, the result showed that the treatment of 90 % of filed capacity (W3) seemed to be better adapted to product a high crop yield with acceptable yield coupling with water use efficiency in Golestan province.

Keywords: deficit irrigation, water use efficiency, yield, soybean

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Authors: Saeed Yazdani, Shahrbanoo Bagheri, Sepideh Nikravesh

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Considering the importance and scarcity of water resources, the efficient management of water resources is of great importance. Adoption of modern irrigation technology is considered to be a key of increasing the efficiency of water used in agriculture. Policy makers have implemented several ways to induce the adoption of new irrigation technology. The empirical studies show that farmers are reluctant to utilize the use of new irrigation methods. This study aims to assess factors affecting on farmer’s decision on the application of water saving technologies with emphasize on crop price variation and water sources. A Logit model was employed to examine the impact of different variables on use of water saving technology. The required data gathered from a sample of 204 farmers in the year 2012. The results indicate that different variables such as crop price variability, water supply source, high-value crops, farm size, income, education, membership in cooperatives have a positive effect and variables such as age and number of plots have a negative impact on the probability of adopting modern water saving technologies.

Keywords: irrigation, water, water saving technology, scarcity

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Authors: Alfred L. Guiffrida

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A review of the literature on supply chain delivery models which use delivery windows to measure delivery performance is presented. The review herein serves to meet the following objectives: (i) provide a synthesis of previously published literature on supply chain delivery performance models, (ii) provide in one paper a consolidation of research that can serve as a single source to keep researchers up to date with the research developments in supply chain delivery models, and (iii) identify gaps in the modeling of supply chain delivery performance which could stimulate new research agendas.

Keywords: delivery performance, delivery window, supply chain delivery models, supply chain performance

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Authors: Muhammad Zafarullah Khan, Sumeera Abbasi

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The Farmers Field School (FFS) aims at benefiting poor farmers by improving their knowledge of existing agricultural technologies and integrated crop management to become independent and confident in their decision. The study on effect of farmer’s field school on vegetables production before and after FFS implementation in district Peshawar in four selected villages on each crop in 2011 was conducted from 80 farmers. The results were compared by using paired t-test. It was observed that 80% of the respondents were satisfied with FFS approach as there was a significant increase in vegetable production. The seed rate of tomato and cucumber decreased from 0.185kg/kanal to 0.1 kg/ kanal and 0.120kg/kanal to 0.01kg/kanal while production of tomato and cucumber were increased from 8158.75kgs/kanal to 1030.25kgs/kanal and 3230kgs/kanal to 5340kgs/kanal, respectively after the activities of FFS. FFS brought a positive effect on vegetable production and technology adoption improving their income, skills and knowledge ultimately lead farmers towards empowerment. The input cost including seed, crop management, FYM, and weedicides for tomato were reduced by Rs.28, Rs. 3170 and Rs.658 and cucumber reduced by Rs.35, Rs.570 and Rs.430. Only fertilizers cost was increased by Rs. 2200 in case of tomato and 465 in case of cucumber. FFS facilitator and coordinator should be more skilled and practical oriented to facilitate poor farmers. In light of the above study, more FFS should be planned so that the more farmers should be benefited.

Keywords: effect, farmer field school, vegetables production, integrated crop management

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Authors: Jamshid Qodirov, Sirojiddin Komolov, Ravilov Mirahmad, Olimjon Mirzayev

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Nowadays, natural language processing tools play a crucial role in our daily lives, including various techniques with text processing. There are very advanced models in modern languages, such as English, Russian etc. But, in some languages, such as Uzbek, the NLP models have been developed recently. Thus, there are only a few NLP models in Uzbek language. Moreover, there is no such work that could show which Uzbek NLP model behaves in different situations and when to use them. This work tries to close this gap and compares the Uzbek NLP models existing as of the time this article was written. The authors try to compare the NLP models in two different scenarios: sentiment analysis and sentence similarity, which are the implementations of the two most common problems in the industry: classification and similarity. Another outcome from this work is two datasets for classification and sentence similarity in Uzbek language that we generated ourselves and can be useful in both industry and academia as well.

Keywords: NLP, benchmak, bert, vectorization

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Authors: Manpreet Kaur, Cheol-Hong Min

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The increasing advancement in the robotics equipped with machine vision sensors applied to precision agriculture is a demanding solution for various problems in the agricultural farms. An important issue related with the machine vision system concerns crop row and weed detection. This paper proposes an automatic furrow detection system based on real-time processing for identifying crop rows in maize fields in the presence of weed. This vision system is designed to be installed on the farming vehicles, that is, submitted to gyros, vibration and other undesired movements. The images are captured under image perspective, being affected by above undesired effects. The goal is to identify crop rows for vehicle navigation which includes weed removal, where weeds are identified as plants outside the crop rows. The images quality is affected by different lighting conditions and gaps along the crop rows due to lack of germination and wrong plantation. The proposed image processing method consists of four different processes. First, image segmentation based on HSV (Hue, Saturation, Value) decision tree. The proposed algorithm used HSV color space to discriminate crops, weeds and soil. The region of interest is defined by filtering each of the HSV channels between maximum and minimum threshold values. Then the noises in the images were eliminated by the means of hybrid median filter. Further, mathematical morphological processes, i.e., erosion to remove smaller objects followed by dilation to gradually enlarge the boundaries of regions of foreground pixels was applied. It enhances the image contrast. To accurately detect the position of crop rows, the region of interest is defined by creating a binary mask. The edge detection and Hough transform were applied to detect lines represented in polar coordinates and furrow directions as accumulations on the angle axis in the Hough space. The experimental results show that the method is effective.

Keywords: furrow detection, morphological, HSV, Hough transform

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Authors: Fitih Ademe, Kibebew Kibret, Sheleme Beyene, Mezgebu Getnet, Gashaw Meteke

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Changes in precipitation, temperature and atmospheric CO2 concentration are expected to alter agricultural productivity patterns worldwide. The interactive effects of soil moisture and nutrient availability are the two key edaphic factors that determine crop yield and are sensitive to climatic changes. The study assessed the potential impacts of climate change on maize yield and corresponding water productivity and nutrient use efficiency under climate change scenarios for the Central Rift Valley of Ethiopia by mid (2041-2070) and end century (2071-2100). Projected impacts were evaluated using climate scenarios generated from four General Circulation Models (GCMs) dynamically downscaled by the Swedish RCA4 Regional Climate Model (RCM) in combination with two Representative Concentration Pathways (RCP 4.5 and RCP8.5). Decision Support System for Agro-technology Transfer cropping system model (DSSAT-CSM) was used to simulate yield, water and nutrient use for the study periods. Results indicate that rainfed maize yield might decrease on average by 16.5 and 23% by the 2050s and 2080s, respectively, due to climate change. Water productivity is expected to decline on average by 2.2 and 12% in the CRV by mid and end centuries with respect to the baseline. Nutrient uptake and corresponding nutrient use efficiency (NUE) might also be negatively affected by climate change. Phosphorus uptake probably will decrease in the CRV on average by 14.5 to 18% by 2050s, while N uptake may not change significantly at Melkassa. Nitrogen and P use efficiency indicators showed decreases in the range between 8.5 to 10.5% and between 9.3 to 10.5%, respectively, by 2050s relative to the baseline average. The simulation results further indicated that a combination of increased water availability and optimum nutrient application might increase both water productivity and nutrient use efficiency in the changed climate, which can ensure modest production in the future. Potential options that can improve water availability and nutrient uptake should be identified for the study locations using a crop modeling approach.

Keywords: crop model, climate change scenario, nutrient uptake, nutrient use efficiency, water productivity

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Authors: Marian Sorin Ionescu, Olivia Negoita, Cosmin Dobrin

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This scientific communication reports and discusses learning models adaptable to modern business problems and models specific to digital concepts and paradigms. In the PAC (probably approximately correct) learning model approach, in which the learning process begins by receiving a batch of learning examples, the set of learning processes is used to acquire a hypothesis, and when the learning process is fully used, this hypothesis is used in the prediction of new operational examples. For complex business models, a lot of models should be introduced and evaluated to estimate the induced results so that the totality of the results are used to develop a predictive rule, which anticipates the choice of new models. In opposition, for online learning-type processes, there is no separation between the learning (training) and predictive phase. Every time a business model is approached, a test example is considered from the beginning until the prediction of the appearance of a model considered correct from the point of view of the business decision. After choosing choice a part of the business model, the label with the logical value "true" is known. Some of the business models are used as examples of learning (training), which helps to improve the prediction mechanisms for future business models.

Keywords: machine learning, business models, convex analysis, online learning

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Authors: Vaclav Novak, Katerina Krizova, Petr Sarec

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Modern agriculture has to face many issues from which soil degradation and lack of organic matter in the soil are only a few of them. Apart from Climate Change, human utilization of landscape is the cause of a majority part of these problems. Cattle production in Czechia has been reduced by more than half in recent 30 years. However, cattle manure is considered as staple organic fertilizer, and its role in attempts for sustainable agriculture is irreplaceable. This study aims to describe the impact of so-called activators of biological manure transformation (Z´fix, Olmix Group) mainly on physical soil properties but also on crop status. The experiment has been established in 2017; nevertheless, initial measurements of implement draft have been performed before the treated manure application. In 2018, the physical soil properties and crop status (sugar beet) has been determined and compared with the untreated manure and control variant. Significant results have been observed already in the first year, where the implement draft decreased by 9.2 % within the treated manure variant in comparison with the control variant.

Keywords: field experiment, implement draft, vegetation index, sugar beet

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Authors: Vhahangwele Belemu, Isaac Busayo Oluwatayo

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Post-harvest losses pose a serious challenge to smallholder fruit crop farmers, especially in the rural communities of South Africa, affecting their economic livelihoods and food security. This study investigated the post-harvest handling practices and technologies harnessed by smallholder fruit crop farmers in the Vhembe district of Limpopo province, South Africa. Data were collected on a random sample of 224 smallholder fruit crop farmers selected from the four municipalities of the district using a multistage sampling technique. Analytical tools employed include descriptive statistics and the tobit regression model. A descriptive analysis of farmers’ socioeconomic characteristics showed that a sizeable number of these farmers are still in their active working age (mean = 52 years) with more males (63.8%) than their female (36.2%) counterparts. Respondents’ distribution by educational status revealed that only a few of these had no formal education (2.2%), with the majority having secondary education (48.7%). Results of data analysis further revealed that the prominent post-harvest technologies and handling practices harnessed by these farmers include using appropriate harvesting techniques (20.5%), selling at a reduced price (19.6%), transportation consideration (18.3%), cleaning and disinfecting (17.9%), sorting and grading (16.5%), manual cleaning (15.6%) and packaging technique (11.6%) among others. The result of the Tobit regression analysis conducted to examine the determinants of post-harvest technologies and handling practices harnessed showed that age, educational status of respondents, awareness of technology/handling practices, farm size, access to credit, extension contact, and membership of association were the significant factors. The study suggests enhanced awareness creation, access to credit facility and improved access to market as important factors to consider by relevant stakeholders to assist smallholder fruit crop farmers in the study area.

Keywords: fruit crop farmers, handling practices, post harvest losses, smallholder, Vhembe District, South Africa

Procedia PDF Downloads 23

Authors: Marilyn S. Painagan, Willie Jones B. Saliling

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This paper reports an optimized cropping calendar and land suitability for maize in North Cotabato derived from modeling crop productivity over time and space. Using Quantum GIS, eight representative soil types and 0.3o x 0.3o climate grids shapefiles were intersected to form thirty two pedoclimatic zones within the boundaries of the province. Surveys were done to ascertain crop performance and phenological properties on field. Based on these surveys, crop parameters were calibrated specific for a variety of maize. Soil properties and climatic data (daily precipitation, maximum and minimum temperatures) from pedoclimatic zones were loaded to the FAO Aquacrop Water Productivity Model along with the crop properties from field surveys to simulate yield from 1980 to 2010. The average yield per month was computed to come up with the month of planting having the highest and lowest probable yield in a year assuming that all lands were planted with maize. The yield attributes were visualized in the Quantum GIS environment. The study revealed that optimal cropping patterns varied across North Cotabato. Highest probable yield (8000 kg/ha) can be obtained when maize is planted on May and September (sandy clay-loam soils) in the northern part of the province while the lowest probable yield (1000 kg/ha) can be obtained when maize is planted on January, February and March (clay loam soils) at the northern part of the province. Yields are simulated on the basis of varieties currently planted by farmers of North Cotabato. The resulting maps suggest where and when maize is most suitable to achieve high yields. There is a need to ground truth and validate the cropping calendar on field.

Keywords: aquacrop, quantum GIS, maize, cropping calendar, water productivity

Procedia PDF Downloads 222

Authors: Josip Arneric, Blanka Skrabic Peric

Abstract:

Forecasting of volatility, i.e. returns fluctuations, has been a topic of interest to portfolio managers, option traders and market makers in order to get higher profits or less risky positions. Based on the fact that volatility is time varying in high frequency data and that periods of high volatility tend to cluster, the most common used models are GARCH type models. As standard GARCH models show high volatility persistence, i.e. integrated behaviour of the conditional variance, it is difficult the predict volatility using standard GARCH models. Due to practical limitations of these models different approaches have been proposed in the literature, based on Markov switching models. In such situations models in which the parameters are allowed to change over time are more appropriate because they allow some part of the model to depend on the state of the economy. The empirical analysis demonstrates that Markov switching GARCH model resolves the problem of excessive persistence and outperforms uni-regime GARCH models in forecasting volatility for selected emerging markets.

Keywords: emerging markets, Markov switching, GARCH model, transition probabilities

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Authors: E. Benga, T. Tengen, A. Alugongo

Abstract:

Periodic and continuous inventory models are the two classical management tools used to handle inventories. These models have advantages and disadvantages. The implementation of both continuous (r,Q) inventory and periodic (R, S) inventory models in most manufacturing plants comes with higher cost. Such high inventory costs are due to the fact that most manufacturing plants are not flexible enough. Since demand and lead-time are two important variables of every inventory models, their effect on the flexibility of the manufacturing plant matter most. Unfortunately, these effects are not clearly understood by managers. The reason is that the decision parameters of the continuous (r, Q) inventory and periodic (R, S) inventory models are not designed to effectively deal with the issues of uncertainties such as poor manufacturing performances, delivery performance supplies performances. There is, therefore, a need to come up with a predictive and hybrid inventory model that can combine in some sense the feature of the aforementioned inventory models. A linear combination technique is used to hybridize both continuous (r, Q) inventory and periodic (R, S) inventory models. The behavior of such hybrid inventory model is described by a differential equation and then optimized. From the results obtained after simulation, the continuous (r, Q) inventory model is more effective than the periodic (R, S) inventory models in the short run, but this difference changes as time goes by. Because the hybrid inventory model is more cost effective than the continuous (r,Q) inventory and periodic (R, S) inventory models in long run, it should be implemented for strategic decisions.

Keywords: periodic inventory, continuous inventory, hybrid inventory, optimization, manufacturing plant

Procedia PDF Downloads 357