Gross energy requirement in fishing operations

Energy is a key input into the fish harvesting process. Efficient use of energy helps in reducing operational costs and environmental impact, while increasing profits. Energy optimisation is an important aspect of responsible fishing as enunciated in the Code of Conduct for Responsible Fisheries. Gross Energy Requirement (GER) is the sum of all non-renewable energy resources consumed in making available a product or service and is expressed in energy units per physical unit of product or service delivered. GER is a measure of intensity of non-renewable resource use and it reflects the amount of depletion of earth’s inherited store of non-renewable energy in order to create and make available a product or service. In this study, GER in fish harvesting up to the point of landing is estimated in selected fish harvesting systems in the small-mechanised sectors of Indian fisheries and compared with reported results from selected non mechanised and motorised fishing systems to reflect the situation during 1997-1998. Among the fish harvesting systems studied, GER t fish-1 ranged from 5.54 and 5.91 GJ, respectively, for wooden and steel purse seiners powered by 156 hp engines; 6.40 GJ for wooden purse seiner with 235 hp engine; 25.18 GJ for mechanised gillnet/line fishing vessel with 89 hp engines; to 31.40 and 36.97 GJ, respectively, for wooden and steel trawlers powered by 99-106 hp engines.

Studies on Energy Requirement and Conservation in Selected Fish Harvesting Systems

Present work deals with the studies on energy requirement and convervation in selected fish harvesting systems.Modem fishing is one of the most energy intensive methods of food production. Fossil fuels used for motorised and mechanised fishing are nonrenewable and limited. Most of the environmental problems that confront mankind today are connected to the use of energy in one way or another. Code of Conduct for Responsible Fisheries (FAO, 1995) highlights the need for efficient use of energy in the fisheries sector. Information on energy requirement in different fish harvesting systems, based on the principles of energy analysis, is entirely lacking in respect of Indian fisheries. Such an analysis will provide an unbiased decision making support for maximising the yield per unit of non-renewable energy use, from different fishery resource systems, by rational deployment of harvesting systems. In the present study, results of investigations conducted during 1997-2000 on energy requirement in selected fish harvesting systems and approaches to energy conservation in fishing, are presented along with a detailed description of the fish harvesting systems and their operation. The content of the thesis is organised into 8 Chapters.

Dietary energy requirement of piracanjuba fingerlings, Brycon orbignyanus, and relative utilization of dietary carbohydrate and lipid

Ten isonitrogenous casein-gelatin-based diets were formulated to contain five estimated metabolizable energy concentrations (10.92, 12.29, 13.63, 14.82 and 16.16 kJ g -1) at two carbohydrate-to-lipid ratios (CHO : L, 5.3 and 12.8, g : g) in a 5 × 2 factorial arrangement. Each diet was assigned to triplicate groups of 11 piracanjuba fingerlings (5.25 ± 0.14 g) and fed to apparent satiation twice a day for 90 days. Higher daily weight gain was obtained by fish fed the 13.63 kJ g -1 diets for both CHO : L ratios. There was a significant reduction of feed consumption when dietary energy concentration increased above 13.63 kJ g -1. Feed conversion ratio and apparent net energy retention improved as dietary energy increased. Apparent net protein retention tended to be lower in the highest and lowest dietary energy concentrations. The results suggest that dietary lipid energy was more efficiently utilized by piracanjuba fingerlings than carbohydrate energy. Body composition and hepatosomatic index (HSI) were not influenced by dietary CHO : L ratio. However, an increase in dietary energy concentration beyond 13.63 kJ g -1 resulted in a significant increment in lipid deposition, while body moisture and HSI decreased. Our findings indicate that at 300 g kg -1 dietary crude protein, a CHO : L ratio of 5.3 is recommended for piracanjuba, and the required energy is either 13.63 kJ g -1 if raised for aquaculture or 14.82 kJ g -1 if destined to stock enhancement. © 2006 Blackwell Publishing Ltd.

The energy requirement of farm women and other nutrition studies.

Mimeographed.

Rural energy consumption patterns - A field study

This paper is a condensed version of the final report of a detailed field study of rural energy consumption patterns in six villages located west of Bangalore in the dry belt of Karnataka State in India. The study was carried out in two phases; first, a pilot study of four villages and second, the detailed study of six villages, the populations of which varied from around 350 to about 950. The pilot survey ended in late 1976, and most of the data was collected for the main project in 1977. Processing of the collected data was completed in 1980. The aim was to carry out a census survey, rather than a sample study. Hence, considerable effort was expended in production of both a suitable questionnaire, ensuring that all respondents were contacted, and devising methods which would accurately reflect the actual energy use in various energy-utilising activities. In the end, 560 households out of 578 (97%) were surveyed. The following ranking was found for the various energy sources in order of average percentage contribution to the annual total energy requirement: firewood, 81·6%; human energy, 7·7%; animal energy, 2·7%; kerosene, 2·1%; electricity, 0·6% and all other sources (rice husks, agro-wastes, coal and diesel fuel), 5·3%. In other words commercial fuels made only a small contribution to the overall energy use. It should be noted that dung cakes are not burned in this region. The average energy use pattern, sector by sector, again on a percentage basis, was as follows: domestic, 88·3%; industry, 4·7%; agriculture, 4·3%; lighting, 2·2% and transport, 0·5%. The total annual per capita energy consumption was 12·6 ± 1·2 GJ, giving an average annual household consumption of around 78·6 GJ.

Rural energy consumption patterns - A field study

This paper is a condensed version of the final report of a detailed field study of rural energy consumption patterns in six villages located west of Bangalore in the dry belt of Karnataka State in India. The study was carried out in two phases; first, a pilot study of four villages and second, the detailed study of six villages, the populations of which varied from around 350 to about 950. The pilot survey ended in late 1976, and most of the data was collected for the main project in 1977. Processing of the collected data was completed in 1980. The aim was to carry out a census survey, rather than a sample study. Hence, considerable effort was expended in production of both a suitable questionnaire, ensuring that all respondents were contacted, and devising methods which would accurately reflect the actual energy use in various energy-utilising activities. In the end, 560 households out of 578 (97%) were surveyed. The following ranking was found for the various energy sources in order of average percentage contribution to the annual total energy requirement: firewood, 81A·6%; human energy, 7A·7%; animal energy, 2A·7%; kerosene, 2A·1%; electricity, 0A·6% and all other sources (rice husks, agro-wastes, coal and diesel fuel), 5A·3%. In other words commercial fuels made only a small contribution to the overall energy use. It should be noted that dung cakes are not burned in this region. The average energy use pattern, sector by sector, again on a percentage basis, was as follows: domestic, 88A·3%; industry, 4A·7%; agriculture, 4A·3%; lighting, 2A·2% and transport, 0A·5%. The total annual per capita energy consumption was 12A·6 A± 1A·2 GJ, giving an average annual household consumption of around 78A·6 GJ.

Solar energy decision support system

Energy plays a prominent role in human society. As a result of technological and industrial development,the demand for energy is rapidly increasing. Existing power sources that are mainly fossil fuel based are leaving an unacceptable legacy of waste and pollution apart from diminishing stock of fuels.Hence, the focus is now shifted to large-scale propagation of renewable energy. Renewable energy technologies are clean sources of energy that have a much lower environmental impact than conventional energy technologies. Solar energy is one such renewable energy. Most renewable energy comes either directly or indirectly from the sun. Estimation of solar energy potential of a region requires detailed solar radiation climatology, and it is necessary to collect extensive radiation data of high accuracy covering all climatic zones of the region. In this regard, a decision support system (DSS)would help in estimating solar energy potential considering the region’s energy requirement.This article explains the design and implementation of DSS for assessment of solar energy. The DSS with executive information systems and reporting tools helps to tap vast data resources and deliver information. The main hypothesis is that this tool can be used to form a core of practical methodology that will result in more resilient in time and can be used by decision-making bodies to assess various scenarios. It also offers means of entering, accessing, and interpreting the information for the purpose of sound decision making.

Energy analysis of the ring seine operations, off Cochin, Kerala

Ring seines are lightly constructed purse seines adapted for operation in the traditional sector. Fish production and energy requirement in the ring seine operations, off Cochin, Kerala, India are discussed in this paper, based on data collected during 1997- 1998. The results reflect the Gross Energy Requirement (GER) situation that existed during 1997-1998. Mean catch per ring seiner per year worked out to be 211.9 t of which sardines (Sardinella spp.) constituted 44.3%, followed by Indian mackerel (Rastrelliger kanagurta) 29.7%, carangids 11.4%, penaeid prawns 2.2%, pomfrets 1.1% and miscellaneous fish 11.3%. Total energy inputs into the ring seine operations were estimated to be 1300.8 GJ. Output by way of fish production was determined to be 931.85 GJ. GER is the sum of all non-renewable energy resources consumed in making available a product or service and is a measure of intensity of non-renewable resource use. GER per tonne of fish landed by ring seiners was estimated to be 6.14. Among the operational inputs, kerosene constituted 73.4% of the GER, followed by petrol (12.7%), diesel (6.7%) and lubricating oil (2.4%). Fishing gear contributed 3.8%, engine 0.8% and fishing craft 0.3% of the GER. Energy ratio for ring seining was 0.72 and energy intensity 1.40.

Comparison of energy evaluation systems and a mechanistic model for milk production by dairy cattle offered fresh grass-based diets

Grass-based diets are of increasing social-economic importance in dairy cattle farming, but their low supply of glucogenic nutrients may limit the production of milk. Current evaluation systems that assess the energy supply and requirements are based on metabolisable energy (ME) or net energy (NE). These systems do not consider the characteristics of the energy delivering nutrients. In contrast, mechanistic models take into account the site of digestion, the type of nutrient absorbed and the type of nutrient required for production of milk constituents, and may therefore give a better prediction of supply and requirement of nutrients. The objective of the present study is to compare the ability of three energy evaluation systems, viz. the Dutch NE system, the agricultural and food research council (AFRC) ME system, and the feed into milk (FIM) ME system, and of a mechanistic model based on Dijkstra et al. [Simulation of digestion in cattle fed sugar cane: prediction of nutrient supply for milk production with locally available supplements. J. Agric. Sci., Cambridge 127, 247-60] and Mills et al. [A mechanistic model of whole-tract digestion and methanogenesis in the lactating dairy cow: model development, evaluation and application. J. Anim. Sci. 79, 1584-97] to predict the feed value of grass-based diets for milk production. The dataset for evaluation consists of 41 treatments of grass-based diets (at least 0.75 g ryegrass/g diet on DM basis). For each model, the predicted energy or nutrient supply, based on observed intake, was compared with predicted requirement based on observed performance. Assessment of the error of energy or nutrient supply relative to requirement is made by calculation of mean square prediction error (MSPE) and by concordance correlation coefficient (CCC). All energy evaluation systems predicted energy requirement to be lower (6-11%) than energy supply. The root MSPE (expressed as a proportion of the supply) was lowest for the mechanistic model (0.061), followed by the Dutch NE system (0.082), FIM ME system (0.097) and AFRCME system(0.118). For the energy evaluation systems, the error due to overall bias of prediction dominated the MSPE, whereas for the mechanistic model, proportionally 0.76 of MSPE was due to random variation. CCC analysis confirmed the higher accuracy and precision of the mechanistic model compared with energy evaluation systems. The error of prediction was positively related to grass protein content for the Dutch NE system, and was also positively related to grass DMI level for all models. In conclusion, current energy evaluation systems overestimate energy supply relative to energy requirement on grass-based diets for dairy cattle. The mechanistic model predicted glucogenic nutrients to limit performance of dairy cattle on grass-based diets, and proved to be more accurate and precise than the energy systems. The mechanistic model could be improved by allowing glucose maintenance and utilization requirements parameters to be variable. (C) 2007 Elsevier B.V. All rights reserved.

A comparative evaluation of functions for describing the relationship between live-weight gain and metabolizable energy intake in turkeys

The suitability of models specifically re-parameterized for analyzing energy balance data relating metabolizable energy intake to growth rate has recently been investigated in male broilers. In this study, the more adequate of those models was applied to growing turkeys to provide estimates of their energy needs for maintenance and growth. Three functional forms were used. They were: two equations representing diminishing returns behaviour (monomolecular and rectangular hyperbola); and one equation describing smooth sigmoidal behaviour with a fixed point of inflexion (Gompertz). The models estimated the metabolizable energy requirement for maintenance in turkeys to be 359-415 kJ/kg of live-weight/day. The predicted values of average net energy requirement for producing 1 g of gain in live-weight, between 1 and 4 times maintenance, varied from 8.7 to 10.9 kJ. These results and those previously reported for broilers are a basis for accepting the general validity of these models.

Protein Intake during Weight Loss Influences the Energy Required for Weight Loss and Maintenance in Cats

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Modeling energy utilization in broiler breeders, laying hens and broilers

The factorial approach has been used to partition the energy requirements into maintenance, growth, and production. The coefficients determined for these purposes can be used to elaborate energy requirement models. These models consider the body weight, weight gain, egg production, and environmental temperature to determine the energy requirements for poultry. Predicting daily energy requirement models can help to establish better and more profitable feeding programs for poultry. Studies were conducted at UNESP-Jaboticabal to determine metabolizable energy (ME) requirement models for broiler breeders, laying hens, and broilers. These models were evaluated in performance trials and provided good adjustments. Therefore, they could be used to establish nutritional programs. This review aims to outline the results found at UNESP studies and to show the application of models in nutritional programs for broiler breeders, laying hens, and broilers.