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Trends on the Artificial Fertilizer Market and in Fertilizers Use in Hungary
5-12Views:228The fertilizer market in Hungary is rather concentrated, which has a strong influence on the price of the fertilizer. Our domestic fertilizer use is primarily determined by that of nitrogen. The use of phosphorus is also significant but the trends in the use of potassium do not match the total quantities applied in individual years. Consequently, it can be concluded that the majority of farmers still focus on the application of nitrogen and also apply phosphorus but either neglect or do not pay enough attention to potassium fertilization. The changes in fertilizer prices between 2006 and 2017 can be broken down into two periods. Until 2012 a very important and dynamic increase was observed as a result of which the prices of N, P and K fertilizers increased by 80-120%, 160% and about 120%, respectively. This was followed by a downturn in the market and in relation to 2012 prices there were 20-30/ decreases experienced until 2017 but the rate of this lagged behind the prices in other European countries. Owing to this trend the prices of N, P and K have increased by 60%, 100% and 80%, respectively, over the past ten years. The correlation between fertilizer application and the prices of fertilizers in any given year is low but there is a positive one observed between fertilizer application and the fertilizer prices in the preceding year. This means supposedly that farmers mostly buy the fertilizers they wish to apply not in the current but in the preceding year and store them until these are applied. There is a strong correlation seen between fertilizer prices and the prices of corn and wheat, which means that fertilizer traders also keep tabs on economic results and also increase fertilizer prices under the influence of higher prices. Furthermore, it can be claimed that there is no correlation between crude oil prices on the world market and domestic N fertilizer prices. This is an important factor since the primary base material of N fertilizers is natural gas and their production involves considerable energy costs as well. It can be seen, however, that this is not what determines our domestic fertilizer prices, which can be explained by the fact that the price calculations by the determining actors on the Hungarian fertilizer market is not based on costs but on the demand.
JEL Classification: Q13
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Changes in costs of precision nutrition depending on crop rotation
59-63Views:121By applying precision nutrition the yield heterogeneity owing to the different features of soil spots can be taken into consideration. The planned and sprayed fertilizer adjusted to the expected yield rendered to soil spots can reduce the negative effects of artificial chemicals on soil and environment. The aim of this paper is to examine how the quantity and the cost of fertilizer (material and operational) will change on spot level on a certain plot during a five-year period, considering crop rotation, too. The following crops are in the rotation: winter wheat, corn and sunflower. Precision nutrition can be used in all the cultures mentioned above. Our earlier (static) model calculations have revealed that the threshold price of precision production was lower by 31% than in conventional technology. So it is necessary to explore for a longer period how the profitability of precision nutrition reacts to the changes in input and yield prices in different crops. The risk receptivity of precision nutrition can be characterized with the help of price sensitive analyses. Effects on profitability of other technological elements are not analysed in this paper.
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The analysis of agro-economic effects of household food wastage through the example of bread
9-18Views:202In our busy world, where numerous people starve and where the resources are restricted, it is a key issue to pay particular attention to the topic of prevention and decrease of food loss as well as food wastage.Wastage of food produced and delivered to the end user (customer) is an issue arising globally and nationally as well, which results in efficiency loss at economic level in any case. While the FAO study mentions food waste of the order of 1.3 billion tonnes on a world scale, then the annual quantity of food waste in Hungary is estimated at about 1.8 million tonnes, which contains the waste of every member of the chain from production to consumption. On the basis of the data published by the Hungarian Food Bank (2015), the amount of food waste caused by the population is 400 000 tonnes. In compliance with our objectives, inputs – expressed by non-financial and financial indicators – emerge during production are assigned to the quantity of wasted food. Applying the aforementioned method we would like to make customers realize how many resources (land, water, artificial fertilizer, pesticide, seed and gasoil) are utilized needlessly in food verticum by the end products – at present by different breads they throw out. As our calculations prove by 10% waste of breads the utilization of 5 300 hectares of wheat land and 660 hectares of rye land can be considered unnecessary. By 10% waste of breads the financial value of the utilized resources is altogether 3.25 million EUR. Out of this the financial value of utilized artificial fertilizer is 1.10 million EUR (34%), of utilized pesticide is 1.15 million EUR (35%), of utilized gasoil is 0.70 million EUR (22%) and of utilized seed is 0.30 million EUR (9%). Among different breads, white bread is purchased in the greatest volume by the Hungarian households, from which 121 900 tonnes are bought annually on an average. This quantity is equal to almost the 40% of the annual bread sell. If 10% of purchased white bread is thrown out, it results in useless utilization of 2 676 hectares of wheat land in food verticum. The quantity of utilized water arising form wastage is 15.8 million m3. Further losses emerge as regards material inputs: artificial fertilizer- to the value of 0.50 million EUR, pesticide- to the value of 0.58 million EUR, seed to the value of 0.15 million EUR and gasoil-loss to the value of circa 0.35 million EUR. Totally, material input to the value of 1.58 million EUR is owing to the Hungarian households in case of 10% white bread wastage.
JEL code: Q53
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The effects of climate change on cereals yield of production and food security in Gambia
83-92Views:875Increasingly, empirical evidences are substantiating the effects of climate change on agricultural production is a reality. In the early part of the 20th century many were skeptical about the so-called climate change that is due to global warming. The Intergovernmental Panel on Climate Change (IPCC, 2007) defines climate change as follows: “climate change refers to a change in the state of the climate that can be identified by changes in the mean or variability of its properties and that persists for extended periods, typically decades or longer” This study analyses the impact of climate change on cereals production (millet and maize) in the Gambia using a time series data for a period of 46 years (1960 – 2013) at an aggregate level to assess the relationship between climate (temperatures and rainfall,) and non-climate variables fertilizer, area planted respectively and yield. The specific objectives of the research are: (1) How climate change affects the expected cereals (Millet and Maize) output or yield in the Gambia. (2) How the level of output risk within cereals (Millet and Maize) farming is affected? In order to achieve these set objectives, the paper will adopt Just and Pope modified Ricardian production functions for climate change impact assessments (e.g., Chen et al. 2004), the paper will also control for the impacts of regular input factors in the production process. The study used a data set for the Gambia comprising variables relevant for cereals production and climate information from 1960 through 2013. There is strong evidence that climate will affects Maize and Millet; according to the analysis 77% and 44% of the variability in the yield of Maize and Millet respectively is explained by the climate and non-climate variables included in the model. Given the effects of climate variables on cereals production, and increasing climate change vulnerabilities on other food production section, the result of this paper will add voice to the growing call for policy makers to step up funding in research and development in climate change adaptation and mitigation.
JEL classification: Q54
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Interior point algorithm for solving farm resource allocation problem
45-49Views:169This paper introduces interior point algorithm as an alternative approach to simplex algorithm for solving farm resource allocation problem. The empirical result of interior point algorithm is compared with that of the simplex algorithm. It goes further to address a profit maximization problem. The result revealed several relevant patterns. Results of the interior point algorithm is similar to that of the simplex algorithm. Findings indicated that in both algorithms, the farm is to produce peppers, wheat which is irrigated and weeded manually, hire additional month of labour, and also purchase urea and muriate fertilizer to realize a similar amount of profit. Additionally, both algorithms suggested that practicing crop rotation where beans, if grown, should be altered with wheat cannot be possible since no beans will be grown. The Simplex algorithm saves 39 iterations over Interior Point algorithm in solving the farm resource allocation problem. The findings demonstrate that the interior point algorithm offers a useful alternative to the simplex algorithm when addressing farm resource allocation problem.
JEL code: D24, D57, C61, C63, C67
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Optimal crop plan of cooperative farmers in Osun state, Nigeria: a linear programming approach
Views:204Optimal level of production requires better use of existing resources at the lowest possible cost. Despite the inherent advantage of cooperatives to the agricultural sector, the question of how farmers under cooperative umbrella use farm resource for optimal outcome remains unanswered. This study investigates optimal crop mix for cooperative farmers in rural communities in Southwest Nigeria. Primary data were collected for the study through structured questionnaire. The data were fitted to Linear Programming Model. Three different cropping patterns are identified among the cooperative farmers. Based on the results from linear programming model, only maize, cassava and yam are admitted in the final plan and this combination is to be produced at 2.23 hectares. The gross margin value associated with the plan is ₦156, 235.781 (1$ = N365). Input resources such as land, labour, fertilizer, and chemicals are not fully utilized. The slack values for these inputs are 0.31, 651.20, 1929.6 and 140.76 respectively. The sensitivity analysis shows that seed/seedling is the only binding resource in the final plan with a shadow price which suggests that proper allocation of seed and seedlings would improve returns to cooperative farmers. There is need for appropriate farm management strategies to ensure optimal return for farmers. More education and training is suggested to boost cooperative farmers understanding of optimum strategy that is needed to improve production and earnings.
JEL code: Q10, Q13
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Adaptations to potential impacts of climate change in the “New Hungary” Rural Development Programme
133-137Views:125There are evidences that the climate is changing and the effects on agriculture and wildlife are discernible. Spring is occurring earlier and autumn later, all of which have impacts on agriculture and forestry. Climate change is also predicted to result in more frequent droughts, increased flooding in Hungary, but the relationship between agriculture and climate change is more complex. Climate change has physical effects on farming and farm based wildlife. Agriculture needs to adapt to climate change by exploring, which crops and farming systems are best adapted to the changed conditions. Land management also needs to adapt to preserve biodiversity by protecting valuable habitats and species and helping them in the changing environment. With better management, agriculture and forestry can also mitigate climate change by reducing direct greenhouse gas emissions from land use, land use change and forestry, by producing crops as a source of renewable energy and by protecting carbon stored in soils and in manure. The HRDP comprises of a series of funding based on the following overarching priorities: (i) enhance the environment and countryside, (ii) making agriculture and forestry more competitive and sustainable, (iii) enhancing opportunity in rural areas, whether in the farming sector or the broader rural economy. Actions discussed in this paper are based on the New Hungary Rural Development Programme (2007–2013) and focused on reducing the effects of climate change in rural area. Establishment of agro-forestry systems and integrated pest management help mitigation goals and increase climate change adaptation potential. Minimizing unwanted side effects of agriculture by reducing the use of fertilizer and increasing the safety for environment (soil, water, and air) and human health have positive effects on adaptation potential. Restoration of agricultural production though diversification of agriculture and pastures management, improvement in drain age and irrigation equipment are good examples of adaptation for climate change. Integrated production, which is oriented to controlled cultivation of crops, vine, fruits and vegetables, and improvement of animal rearing conditions to increase production standards and overall welfare are preferred and ecologically sound methods of adaptation.
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Technical efficiency analysis of maize production: evidence from Ghana
73-79Views:470The study applies the single-stage modelling stochastic frontier approach to investigate the performance of maize farmers in the Ejura-Sekyedumase District of Ghana. It estimates the level of technical efficiency and its determinants for 306 maize farmers. Findings indicated that land, labour and fertilizer influenced output positively whilst agrochemicals and seeds affected output negatively. A wide variation in output was also found among producers of maize. The study further revealed that age, sex and off-farm work activities were significant determinants of technical inefficiencies in production. Results from the maximum likelihood estimate of the frontier model showed that averagely, farmers were 67% technically efficient, implying that 33% of maize yield was not realized. The return to scale which measures the productivity level of farmers was 1.22, suggesting that the farmers are operating at an increasing returns to scale.
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