889 resultados para Agricultural production indicators
Resumo:
This paper reviews the concept of “organic”, its meaning and emphasizes a comparison with conventional goods. It develops the background of organic goods in the past 20 years, quotations different definitions of organic and developing a main definition. Also it states certain criteriab and variables in order to develop a deeper business analysis. And it has the objective to define the advantages, disadvantages, key points and strategies for companies that want to venture an organic production, and if it’s recommendable to pursue. After a cross case and SWOT analysis it is possible to determine that depending of the core strategy and type of company if an enterprise can decide to venture the organic market.
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In the ornamental plant production region of Girona (Spain), which is one of the largest of its kind in southern Europe, most of the surface is irrigated using wide blocked-end furrows. The objectives of this paper were: (1) to evaluate the irrigation scheduling methods used by ornamental plant producers; (2) to analyse different scenarios in order to assess how they affect irrigation performance; (3) to evaluate the risk of deep percolation; and (4) to calculate gross water productivity. A two-year study in a representative commercial field, planted with Prunus cerasifera ‘Nigra’, was carried out. The irrigation dose applied by the farmers was slightly smaller than the required water dose estimated by the use of two different methods: the first based on soil water content, and the second based on evapotranspiration. Distribution uniformity and application efficiency were high, with mean values above 87%. Soil water content measurements revealed that even at the end of the furrow, where the infiltrated water depth was greatest, more than 90% of the infiltrated water was retained in the shallowest 40 cm of the soil; accordingly, the risk of water loss due to deep percolation was minimal. Gross water productivity for ornamental tree production was € 11.70 m–3, approximately 20 times higher than that obtained with maize in the same region
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The Aspen Parkland of Canada is one of the most important breeding areas for temperate nesting ducks in North America. The region is dominated by agricultural land use, with approximately 9.3 million ha in pasture land for cattle grazing. However, the effects of using land for cattle grazing on upland-nesting duck production are poorly understood. The current study was undertaken during 2001 and 2002 to investigate how nest density and nesting success of upland-nesting ducks varied with respect to the intensity of cattle grazing in the Aspen Parkland. We predicted that the removal and trampling of vegetation through cattle grazing would reduce duck nest density. Both positive and negative responses of duck nesting success to grazing have been reported in previous studies, leading us to test competing hypotheses that nesting success would (1) decline linearly with grazing intensity or (2) peak at moderate levels of grazing. Nearly 3300 ha of upland cover were searched during the study. Despite extensive and severe drought, nest searches located 302 duck nests. As predicted, nest density was higher in fields with lower grazing intensity and higher pasture health scores. A lightly grazed field with a pasture score of 85 out of a possible 100 was predicted to have 16.1 nests/100 ha (95% CI = 11.7–22.1), more than five times the predicted nest density of a heavily grazed field with a pasture score of 58 (3.3 nests/100 ha, 95% CI = 2.2–4.5). Nesting success was positively related to nest-site vegetation density across most levels of grazing intensity studied, supporting our hypothesis that reductions in vegetation caused by grazing would negatively affect nesting success. However, nesting success increased with grazing intensity at the field scale. For example, nesting success for a well-concealed nest in a lightly grazed field was 11.6% (95% CI = 3.6–25.0%), whereas nesting success for a nest with the same level of nest-site vegetation in a heavily grazed field was 33.9% (95% CI = 17.0–51.8%). Across the range of residual cover observed in this study, nests with above-average nest-site vegetation density had nesting success rates that exceeded the levels believed necessary to maintain duck populations. Our findings on complex and previously unreported relationships between grazing, nest density, and nesting success provide useful insights into the management and conservation of ground-nesting grassland birds.
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Mega-scale glacial lineations (MSGLs) are longitudinally aligned corrugations (ridge-groove structures 6-100 km long) in sediment produced subglacially. They are indicators of fast flow and a common signature of ice-stream beds. We develop a qualitative theory that accounts for their formation, and use numerical modelling, and observations of ice-stream beds to provide supporting evidence. Ice in contact with a rough (scale of 10-10(3) m) bedrock surface will mimic the form of the bed. Because of flow acceleration and convergence in ice-stream onset zones, the ice-base roughness elements experience transverse strain, transforming them from irregular bumps into longitudinally aligned keels of ice protruding downwards. Where such keels slide across a soft sedimentary bed, they plough through the sediments, carving elongate grooves, and deforming material up into intervening ridges. This explains MSGLs and has important implications for ice-stream mechanics. Groove ploughing provides the means to acquire new lubricating sediment and to transport large volumes of it downstream. Keels may provide basal drag in the force budget of ice streams, thereby playing a role in flow regulation and stability We speculate that groove ploughing permits significant ice-stream widening, thus facilitating high-magnitude ice discharge.
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Yarn minisett technique (YMT) has been promoted throughout West Africa since the 1980s as a sustainable means of producing clean yarn planting material, but adoption of the technique is Often reported as being patchy at best. While there has been much research Oil the factors that influence adoption of the technique, there have been no attempts to assess its economic viability under 'farmer-managed' as distinct from 'on station' conditions. The present paper describes the results of farmer-managed trials employing the YMT (white yarn: Dioscorea rotundata) at two villages in Igalaland, Kogi State, Nigeria. One of the villages (Edeke) is on the banks of the River Niger and represents it specialist yarn environment, whereas the other village (Ekwuloko) is inland, where farmers employ a more general cropping system. Four farmers were selected in each of the two villages and asked to plant a trial comprising two varieties of yam, their popular local variety its well its another variety grown in other parts of Igalaland, and to treat yarn setts (80-100 g) with either woodash or insecticide/nematicide + fungicide mix (chemical treatment). Results suggest that while chemical sett treatment increased yield and hence gross margin compared with woodash, if household labour is costed then YMT is not economically viable. However, the specialist yarn growers of Edeke were far more positive about the use of YMT as they tended to keep the yarn seed tubers for planting rather than sell them. Thus, great care needs to be taken with planning adoption surveys on the assumption that all farmers should adopt a technology.
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Agricultural management of grassland in lowland Britain has changed fundamentally in the last 50 years, resulting in spatial and structural uniformity within the pastoral landscape. The full extent to which these changes may have reduced the suitability of grassland as foraging habitat for birds is unknown. This study investigated the mechanisms by which these changes have impacted on birds and their food supplies. We quantified field use by birds in summer and winter in two grassland areas of lowland England (Devon and Buckinghamshire) over 3 years, relating bird occurrence to the management, sward structure and seed and invertebrate food resources of individual fields. Management intensity was defined in terms of annual nitrogen input. There was no consistent effect of management intensity on total seed head production, although those of grasses generally increased with inputs while forbs were rare throughout. Relationships between management intensity and abundance of soil and epigeal invertebrates were complex. Soil beetle larvae were consistently lower in abundance, and surface-active beetle larvae counts consistently higher, in intensively managed fields. Foliar invertebrates showed more consistent negatively relationships with management intensity. Most bird species occurred at low densities. There were consistent relationships across regions and years between the occurrence of birds and measures of field management. In winter, there was a tendency towards higher occupancy of intensively managed fields by species feeding on soil invertebrates. In summer, there were few such relationships, although many species avoided fields with tall swards. Use of fields by birds was generally not related to measures of seed or invertebrate food abundance. While granivorous species were perhaps too rare to detect a relationship, in insectivores the strong negative relationships (in summer) with sward height suggested that access to food may be the critical factor. While it appears that intensification of grassland management has been deleterious to the summer food resources of insectivorous birds that use insects living within the grass sward, intensification may have been beneficial to several species in winter through the enhancement of soil invertebrates. Synthesis and applications. We suggest that attempts to restore habitat quality for birds in grassland landscapes need to create a range of management intensities and sward structures at the field and farm scales. A greater understanding of methods to enhance prey accessibility, as well as abundance, for insectivorous birds is required.
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A model of sugarcane digestion was applied to indicate the suitability of various locally available supplements for enhancing milk production of Indian crossbred dairy cattle. Milk production was calculated according to simulated energy, lipogenic, glucogenic and aminogenic substrate availability. The model identified the most limiting substrate for milk production from different sugarcane-based diets. For sugarcane tops/urea fed alone, milk production was most limited by amino acid followed by long chain fatty acid availability. Among the protein-rich oil cake supplements at 100, 200 and 300 g supplement/kg total DM, cottonseed oil cake proved superior with a milk yield of 5.5, 7.3 and 8.3 kg/day, respectively. This was followed by mustard oil cake with 5.1, 6.5 and 7.6 kg/day, respectively. In the case of a protein-rich supplement (fish meal), milk yield was limited to 6.6 kg/day due to a shortage of long chain fatty acids. However, at 300 g of supplementation, energy became limiting, with a milk yield of 6.7 kg/day. Supplementation with rice bran and rice polishings at 100, 200 and 300 g restricted milk yield to 4.3, 4.9 and 5.5 and 4.5, 5.3 and 6.1 kg/day, respectively, and amino acids became the factor limiting milk production. The diet comprising basal sugarcane tops supplemented by leguminous fodder, dry fodder (e.g. rice or wheat straw) and concentrates at levels of 100, 200 and 300 g supplements/kg total diet DM proved to be the most balanced with a milk yield of 5.1, 6.7 and 9.0 kg/day, respectively.
Biosecurity in agriculture: an economic analysis of coexistence of professional and hobby production
Resumo:
One component of biosecurity is protection against invasive alien species, which are one of the most important threats worldwide to native biodiversity and economic profitability in various sectors, including agriculture. However, agricultural producers are not homogeneous. They may have different objectives and priorities, use different technologies, and occupy heterogeneous parcels of land. If the producers differ in terms of their attitude towards invasive pests and the damages they cause, there are probably external effects in the form of pest spread impacts and subsequent damages caused. We study such impacts in the case of two producer types: profit-seeking professional producers and utility-seeking hobby producers. We show that the hobby producer, having first set a breeding ground for the pest, under-invests in pest control. We also discuss potential policy instruments to correct this market failure and highlight the importance of considering different stakeholders and their heterogeneous incentives when designing policies to control invasive alien species.
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In Central Brazil, the long-term sustainability of beef cattle systems is under threat over vast tracts of farming areas, as more than half of the 50 million hectares of sown pastures are suffering from degradation. Overgrazing practised to maintain high stocking rates is regarded as one of the main causes. High stocking rates are deliberate and crucial decisions taken by the farmers, which appear paradoxical, even irrational given the state of knowledge regarding the consequences of overgrazing. The phenomenon however appears inextricably linked with the objectives that farmers hold. In this research those objectives were elicited first and from their ranking two, ‘asset value of cattle (representing cattle ownership)' and ‘present value of economic returns', were chosen to develop an original bi-criteria Compromise Programming model to test various hypotheses postulated to explain the overgrazing behaviour. As part of the model a pasture productivity index is derived to estimate the pasture recovery cost. Different scenarios based on farmers' attitudes towards overgrazing, pasture costs and capital availability were analysed. The results of the model runs show that benefits from holding more cattle can outweigh the increased pasture recovery and maintenance costs. This result undermines the hypothesis that farmers practise overgrazing because they are unaware or uncaring about overgrazing costs. An appropriate approach to the problem of pasture degradation requires information on the economics, and its interplay with farmers' objectives, for a wide range of pasture recovery and maintenance methods. Seen within the context of farmers' objectives, some level of overgrazing appears rational. Advocacy of the simple ‘no overgrazing' rule is an insufficient strategy to maintain the long-term sustainability of the beef production systems in Central Brazil.
Resumo:
In Central Brazil, the long-term, sustainability of beef cattle systems is under threat over vast tracts of farming areas, as more than half of the 50 million hectares of sown pastures are suffering from. degradation. Overgrazing practised to maintain high stocking rates is regarded as one of the main causes. High stocking rates are deliberate and crucial decisions taken by the farmers, which appear paradoxical, even irrational given the state of knowledge regarding the consequences of overgrazing. The phenomenon however appears inextricably linked with the objectives that farmers hold. In this research those objectives were elicited first and from their ranking two, 'asset value of cattle (representing cattle ownership and 'present value of economic returns', were chosen to develop an original bi-criteria Compromise Programming model to test various hypotheses postulated to explain the overgrazing behaviour. As part of the model a pasture productivity index is derived to estimate the pasture recovery cost. Different scenarios based on farmers' attitudes towards overgrazing, pasture costs and capital availability were analysed. The results of the model runs show that benefits from holding more cattle can outweigh the increased pasture recovery and maintenance costs. This result undermines the hypothesis that farmers practise overgrazing because they are unaware or uncaring caring about overgrazing costs. An appropriate approach to the problem of pasture degradation requires information on the economics,and its interplay with farmers' objectives, for a wide range of pasture recovery and maintenance methods. Seen within the context of farmers' objectives, some level of overgrazing appears rational. Advocacy of the simple 'no overgrazing' rule is an insufficient strategy to maintain the long-term sustainability of the beef production systems in Central Brazil. (C) 2004 Elsevier Ltd. All rights reserved.
Resumo:
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.
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Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.
Resumo:
Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.