Energy use pattern and sensitivity analysis of rice production: A case study of Guilane province of Iran

Rice is one of the most important crop supplying the world's population's food. Because of the direct links between energy and crop yields, and food supplies, rice energy analysis is essential. The objective of this study was to evaluate the energy balance between inputs and outputs of rice production in Guilane Province of Iran. Data were collected from 105 rice farmers with face to face questionnaire. A total energy input and output of 39.3 and 60.3 G J ha-1 was observed. Fertiliser and fuel were the highest energy inputs with amount of 14.1 and 11.6 G J ha-1, followed by electricity and seed with 5.2 and 3.1 G J ha-1, respectively. Energy use efficiency, energy productivity, specific energy and net energy were 1.57, 0.09, 11.20 and 21 G J ha-1, respectively. The share of non-renewable energy was almost 89%, while the direct and indirect energy usage based on inputs was approximately equal (49 and 51%, respectively). The econometric model showed that fuel and machinery had a significant effect on rice yield. The marginal physical productivity (MPP) value of fuel and machinery was 0.93 and 0.23, respectively. The total cost of production, gross and net returns were 3156, 1629 and 927 US ha-1, respectively. The benefit-cost ratio was calculated to be 1.29.Le riz est parmi d'importantes cultures qui fournissent de la nourriture aux populations du monde. A cause des liens directs entre l'\ue9nergie et les rendements de cultures, l'analyse de l'\ue9nergie pour le riz est primordial. L'objectif de cette \ue9tude \ue9tait d'\ue9valuer la balance \ue9nerg\ue9tique entre apports et sorties de la production du riz dans la Province de Guilane en Iran. De donn\ue9es \ue9taient recuillies de 105 riziculteurs \ue0 l'aide d'un questionnaire face \ue0 face. Un total d'apport et sortie d'\ue9nergie de 39.3 et 60.3 G J ha-1 \ue9tait respectivement observ\ue9. Les fertilisants et le carburant constituaient un apport plus \ue9lev\ue9 d'\ue9nergie de l'ordre de 14.1 et 11.6 G J ha-1 suivis de l'\ue9lecticit\ue9 et semence avec 5.2 et 3.1 G J ha-1, respectivement. L'utilisation efficiente de l'\ue9nergie, la productivit\ue9 de l'\ue9nergie, l'\ue9nergie sp\ue9cifique et l' \ue9nergie nette \ue9taient de 1.57, 0.09, 11.20 et 21 G J ha-1, respectivement. La part de l'\ue9nergie non renouvelable \ue9tait d'environ 89%, pendant que l'usage direct et indirect de l'\ue9nergie bas\ue9 sur les apports \ue9tait approximativement \ue9gal (49 et 51%, respectivement). Le mod\ue8le \ue9conom\ue9trique avait montr\ue9 que le carburant et les machines avaient 0.93 et 0.23, respectivement. Le co\ufbt total de production, le gros et le revenu net \ue9taient de 3156, 1629 et 927 US ha-1, respectivement. Le rapport co\ufbt-b\ue9n\ue9fice calcul\ue9 \ue9tait de 1.29

Energy use pattern and sensitivity analysis of rice production: A case study of Guilane province of Iran

Rice is one of the most important crop supplying the world's population's food. Because of the direct links between energy and crop yields, and food supplies, rice energy analysis is essential. The objective of this study was to evaluate the energy balance between inputs and outputs of rice production in Guilane Province of Iran. Data were collected from 105 rice farmers with face to face questionnaire. A total energy input and output of 39.3 and 60.3 G J ha-1 was observed. Fertiliser and fuel were the highest energy inputs with amount of 14.1 and 11.6 G J ha-1, followed by electricity and seed with 5.2 and 3.1 G J ha-1, respectively. Energy use efficiency, energy productivity, specific energy and net energy were 1.57, 0.09, 11.20 and 21 G J ha-1, respectively. The share of non-renewable energy was almost 89%, while the direct and indirect energy usage based on inputs was approximately equal (49 and 51%, respectively). The econometric model showed that fuel and machinery had a significant effect on rice yield. The marginal physical productivity (MPP) value of fuel and machinery was 0.93 and 0.23, respectively. The total cost of production, gross and net returns were 3156, 1629 and 927 US ha-1, respectively. The benefit-cost ratio was calculated to be 1.29.Le riz est parmi d'importantes cultures qui fournissent de la nourriture aux populations du monde. A cause des liens directs entre l'énergie et les rendements de cultures, l'analyse de l'énergie pour le riz est primordial. L'objectif de cette étude était d'évaluer la balance énergétique entre apports et sorties de la production du riz dans la Province de Guilane en Iran. De données étaient recuillies de 105 riziculteurs à l'aide d'un questionnaire face à face. Un total d'apport et sortie d'énergie de 39.3 et 60.3 G J ha-1 était respectivement observé. Les fertilisants et le carburant constituaient un apport plus élevé d'énergie de l'ordre de 14.1 et 11.6 G J ha-1 suivis de l'électicité et semence avec 5.2 et 3.1 G J ha-1, respectivement. L'utilisation efficiente de l'énergie, la productivité de l'énergie, l'énergie spécifique et l' énergie nette étaient de 1.57, 0.09, 11.20 et 21 G J ha-1, respectivement. La part de l'énergie non renouvelable était d'environ 89%, pendant que l'usage direct et indirect de l'énergie basé sur les apports était approximativement égal (49 et 51%, respectivement). Le modèle économétrique avait montré que le carburant et les machines avaient 0.93 et 0.23, respectivement. Le coût total de production, le gros et le revenu net étaient de 3156, 1629 et 927 US ha-1, respectivement. Le rapport coût-bénéfice calculé était de 1.29

Effluenten van mestverwerkingsinstallaties

This report presents the results of the measuring campaign that was carried out at three types of pig manure processing plants, including reverse osmosis (RO), membrane bioreactior with ultrafiltration (MBR-UF) and evaporation, and at veal manure pre-purification plants. The study was conducted to get a better view of the presence of general classic parameters and precaution parameters (antibiotics, (resistant) bacteria and viruses) in the effluents of the processing plants, and of the purification efficiency of technologies that can be considered as best available techniques (BAT) or equivalent. Additionally, the aim was to establish a reference level for precaution parameters for BAT, to present indicative values for precaution parameters to assess alternative purification techniques for equivalence, and to select indicator parameters for assessing the effectiveness of the applied technique. The implementation of this measuring campaign is a next step to harmonization of the discharge policy for effluents from manure processing plants

In-vitro method and model to estimate methane emissions from liquid manure management on pig and dairy farms in four countries

Methane (CH4) emissions from manure management on livestock farms are a key source of greenhouse gas emissions in some regions and for some production systems, and the opportunities for mitigation may be significant if emissions can be adequately documented. We investigated a method for estimating CH4 emissions from liquid manure (slurry) that is based on anaerobic incubation of slurry collected from commercial farms. Methane production rates were used to derive a parameter of the Arrhenius temperature response function, lnA', representing the CH4 production potential of the slurry at the time of sampling. Results were used for parameterization of an empirical model to estimate annual emissions with daily time steps, where CH4 emissions from individual sources (barns, outside storage tanks) can be calculated separately. A monitoring program was conducted in four countries, i.e., Denmark, Sweden, Germany and the Netherlands, during a 12-month period where slurry was sampled to represent barn and outside storage on finishing pig and dairy farms. Across the four countries, lnA' was higher in pig slurry compared to cattle slurry (p &lt; 0.01), and higher in slurry from barns compared to outside storage (p &lt; 0.01). In a separate evaluation of the incubation method, in-vitro CH4 production rates were comparable with in-situ emissions. The results indicate that lnA' in barns increases with slurry age, probably due to growth or adaptation of the methanogenic microbial community. Using lnA' values determined experimentally, empirical models with daily time steps were constructed for finishing pig and dairy farms and used for scenario analyses. Annual emissions from pig slurry were predicted to be 2.5 times higher than those from cattle slurry. Changing the frequency of slurry export from the barn on the model pig farm from 40 to 7 d intervals reduced total annual CH4 emissions by 46 %; this effect would be much less on cattle farms with natural ventilation. In a scenario with cattle slurry, the empirical model was compared with the current IPCC methodology. The seasonal dynamics were less pronounced, and annual CH4 emissions were lower than with the current methodology, which calls for further investigations. Country-specific models for individual animal categories and point sources could be a tool for assessing CH4 emissions and mitigation potentials at farm level. The project was funded under the 2018 Joint Call of the ERA-NETs FACCE ERA- GAS , SusAn and ICT-AGRI on “Novel technologies, solutions and systems to reduce greenhouse gas emissions in animal production systems”. The Danish contributions to this project were supported by the Ministry of Food, Agriculture and Fisheries through the Green Development and Demonstration Program (contract No. 34009-19-1491). In the Netherlands, the project was supported by the Dutch Research Council ( NWO ) and co-funded by the Ministry of Agriculture, Nature and Food Quality . The Swedish governmental research council Formas supported the Swedish part of the study. In Germany, the project was supported by the German Federal Ministry of Food and Agriculture ( BMEL ) through the Office for Agriculture and Food ( BLE ), Grant No. 2819ERA07A (“M4Models”).</p