885 resultados para Daily yield


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The present work aimed to evaluate udders of Bergamasca ewes and their correlation with milk yield in a mix system of milk yield. Seventy-seven ewes were fed with balanced concentrate starting 20 days before lambing until the end of the experiment. The lambs stayed with their mothers in pastures during the day and were separated at night. They returned to their mothers after the morning milking and were weaned at 45 days of age. Forty-eight hours after lambing, ewes were machine milked once daily at 7 am and the milk yield was recorded for a period of 60 days. Measurements of circumference, depth and width of the udder, and width and length of teats, at 30 and 60 days, were taken. A higher average daily yield of commercial milk was observed after lambs weaning (0.509 vs. 0.435 kg/ewe/day) than before. In the same way, the correlations between udder depth, circumference and width and milk yield were positive and significant only after weaning (0.74, 0.75 and 0.62, respectively). Udder measures had positive correlations with milk yield and can be used in programs of milk yield improvement. (c) 2007 Elsevier B.V. All rights reserved.

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O objetivo deste trabalho é investigar a ancoragem das expectativas de inflação de longo prazo no Brasil, medidas por intermédio das taxas de inflação implícitas nos títulos indexados ao IPCA. Para isso, são extraídas as curvas de juros reais e nominais dos preços do mercado secundário de títulos públicos, e uma vez de posse destes valores, são calculadas as taxas de inflação implícitas observadas diariamente no mercado brasileiro. Utilizando um modelo simples, estimado por Mínimos Quadrados Ordinários (MQO) robusto, testa-se a sensibilidade de alguns vértices das taxas de inflação implícita em relação às variações mensais de indicadores macroeconômicos relevantes para a trajetória de curto prazo da inflação e política monetária. Desta maneira, pretende-se avaliar se o comportamento da inflação implícita nos preços de mercado dos títulos públicos pode oferecer evidências de que as expectativas estão bem ancoradas no Brasil, no âmbito do regime de metas de inflação.

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Este trabalho visa sistematizar um modelo para previsão e explicação dos movimentos de curto prazo da estrutura a termo de taxas de juros pré-fixada em reais do Brasil, baseado na relação dos movimentos em questão com os níveis e alterações que se processam nas variáveis macroeconômicas relevantes. A metodologia usada foi dividir o procedimento em duas etapas: Na primeira etapa, o modelo de Svensson (1994) é usado para ajustar a Estrutura a Termo de Taxas de Juros de cada data específica para obter os parâmetros daquela data. Isso é conseguido através da maximização da estatística R2 na regressão de mínimos quadrados, como sugerido no artigo original de Nelson e Siegel (1987). Então, as medianas dos dois parâmetros de decaimento utilizados são calculadas e mantidas arbitrariamente constantes para facilitar os cálculos da segunda etapa. Na segunda etapa, uma vez que os estimadores que melhor se ajustam às curvas de juros foram obtidos, outra regressão de MQO é realizada considerando os betas de Svensson dependentes de variáveis macroeconômicas de estado.

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

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This study aimed to establish relationships between maize yield and rainfall on different temporal and spatial scales, in order to provide a basis for crop monitoring and modelling. A 16-year series of maize yield and daily rainfall from 11 municipalities and micro-regions of Rio Grande do Sul State was used. Correlation and regression analyses were used to determine associations between crop yield and rainfall for the entire crop cycle, from tasseling to 30 days after, and from 5 days before tasseling to 40 days after. Close relationships between maize yield and rainfall were found, particularly during the reproductive period (45-day period comprising the flowering and grain filling). Relationships were closer on a regional scale than at smaller scales. Implications of the crop-rainfall relationships for crop modelling are discussed.

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The objective of this work was to evaluate the effect of pond management on fish feed, growth, yield, survival, and water and effluent quality, during tambaqui (Colossoma macropomum) juvenile production. Fish were distributed in nine 600 m² earthen ponds, at a density of 8 fish per m²; the rearing period was 60 days. Three different pond management were applied: limed and fertilized (LimFer), limed (Lim), and natural (Nat). Fish were fed with a commercial ration containing 34% crude protein three times daily. There were no significant differences in fish growth or yield. Three main items found in tambaqui stomach were insect, zooplankton and ration, without a significant difference among treatments in proportion. Alkalinity, hardness, and CO2 were greater in LimFer and Lim ponds. Chlorophyll a, transparency, ammonia, nitrite, temperature, and dissolved oxygen of pond water were not significantly different among treatments. Biochemical oxygen demand, total phosphorus, orthophosphate, ammonia, and nitrite were significantly greater in effluents from LimFer ponds. Pond fertilization should be avoided, because growth and yield were similar among the three pond management systems tested; besides, it produces a more impacting effluent.

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The objective of this work was to evaluate the feasibility of simulating maize yield in a sub‑tropical region of southern Brazil using the general large area model (Glam). A 16‑year time series of daily weather data were used. The model was adjusted and tested as an alternative for simulating maize yield at small and large spatial scales. Simulated and observed grain yields were highly correlated (r above 0.8; p<0.01) at large scales (greater than 100,000 km²), with variable and mostly lower correlations (r from 0.65 to 0.87; p<0.1) at small spatial scales (lower than 10,000 km²). Large area models can contribute to monitoring or forecasting regional patterns of variability in maize production in the region, providing a basis for agricultural decision making, and Glam‑Maize is one of the alternatives.

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The objective of this work was to evaluate peduncle and fruit yield in clone MS 076 and in a clonal population of drip-irrigated, early dwarf cashew trees propagated by layering, in six cropping seasons. In order to meet the increased water requirements of the crop resulting from plant growth and development, irrigation during the dry season was performed daily according to the following water regime: 15 min/plant/day during the 1st year, 30 min/plant/day during the 2nd year, 45 min/plant/day during the 3rd year and 60 min/plant/day during all subsequent years. Water was supplied by one drip emitter/plant, at an (adjustable) flow rate of 36 L/h.The research was carried out in Fortaleza-Ceará, Brazil, and a random block design was utilized, with five replicates and split-plots. The clones were assigned to plots and the cropping seasons were considered as subplots. The clonal population was superior to the clone only with regard to number of nut shells (NNS), and solely in the first season. The clone was superior to the population as to NNS and peduncle yield (PY) in the second season, and also with regard to the three evaluated traits - NNS, PY, and nut shell yield, in the last three cropping seasons.

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This study aimed to establish relationships between maize yield and rainfall on different temporal and spatial scales, in order to provide a basis for crop monitoring and modelling. A 16-year series of maize yield and daily rainfall from 11 municipalities and micro-regions of Rio Grande do Sul State was used. Correlation and regression analyses were used to determine associations between crop yield and rainfall for the entire crop cycle, from tasseling to 30 days after, and from 5 days before tasseling to 40 days after. Close relationships between maize yield and rainfall were found, particularly during the reproductive period (45-day period comprising the flowering and grain filling). Relationships were closer on a regional scale than at smaller scales. Implications of the crop-rainfall relationships for crop modelling are discussed.

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Reanalysis data provide an excellent test bed for impacts prediction systems. because they represent an upper limit on the skill of climate models. Indian groundnut (Arachis hypogaea L.) yields have been simulated using the General Large-Area Model (GLAM) for annual crops and the European Centre for Medium-Range Weather Forecasts (ECMWF) 40-yr reanalysis (ERA-40). The ability of ERA-40 to represent the Indian summer monsoon has been examined. The ability of GLAM. when driven with daily ERA-40 data, to model both observed yields and observed relationships between subseasonal weather and yield has been assessed. Mean yields "were simulated well across much of India. Correlations between observed and modeled yields, where these are significant. are comparable to correlations between observed yields and ERA-40 rainfall. Uncertainties due to the input planting window, crop duration, and weather data have been examined. A reduction in the root-mean-square error of simulated yields was achieved by applying bias correction techniques to the precipitation. The stability of the relationship between weather and yield over time has been examined. Weather-yield correlations vary on decadal time scales. and this has direct implications for the accuracy of yield simulations. Analysis of the skewness of both detrended yields and precipitation suggest that nonclimatic factors are partly responsible for this nonstationarity. Evidence from other studies, including data on cereal and pulse yields, indicates that this result is not particular to groundnut yield. The detection and modeling of nonstationary weather-yield relationships emerges from this study as an important part of the process of understanding and predicting the impacts of climate variability and change on crop yields.

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A 2-year longitudinal survey was carried out to investigate factors affecting milk yield in crossbred cows on smallholder farms in and around an urban centre. Sixty farms were visited at approximately 2-week intervals and details of milk yield, body condition score (BCS) and heart girth measurements were collected. Fifteen farms were within the town (U), 23 farms were approximately 5 km from town (SU), and 22 farms approximately 10 km from town (PU). Sources of variation in milk yield were investigated using a general linear model by a stepwise forward selection and backward elimination approach to judge important independent variables. Factors considered for the first step of formulation of the model included location (PU, SU and U), calving season, BCS at calving, at 3 months postpartum and at 6 months postpartum, calving year, herd size category, source of labour (hired and family labour), calf rearing method (bucket and partial suckling) and parity number of the cow. Daily milk yield (including milk sucked by calves) was determined by calving year (p < 0.0001), calf rearing method (p = 0.044) and BCS at calving (p < 0.0001). Only BCS at calving contributed to variation in volume of milk sucked by the calf, lactation length and lactation milk yield. BCS at 3 months after calving was improved on farms where labour was hired (p = 0.041) and BCS change from calving to 6 months was more than twice as likely to be negative on U than SU and PU farms. It was concluded that milk production was predominantly associated with BCS at calving, lactation milk yield increasing quadratically from score 1 to 3. BCS at calving may provide a simple, single indicator of the nutritional status of a cow population.

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Maincrop potato yields in Scotland have increased by 3035 similar to t similar to ha-1 since 1960 as a result of many changes, but has changing climate contributed anything to this? The purpose of this work was to answer this question. Daily weather data for the period 19602006 were analysed for five locations covering the zones of potato growing on the east coast of Scotland (between 55.213 and 57.646 similar to N) to determine trends in temperature, rainfall and solar radiation. A physiologically based potato yield model was validated using data obtained from a long-term field trial in eastern Scotland and then employed to simulate crop development and potential yield at each of the five sites. Over the 47 similar to years, there were significant increases in annual air and 30 similar to cm soil temperatures (0.27 and 0.30 similar to K similar to decade-1, respectively), but no significant changes in annual precipitation or in the timing of the last frost in spring and the first frost of autumn. There was no evidence of any north to south gradient of warming. Simulated emergence and canopy closure became earlier at all five sites over the period with the advance being greater in the north (3.7 and 3.6 similar to days similar to decade-1, respectively) than the south (0.5 and 0.8 similar to days similar to decade-1, respectively). Potential yield increased with time, generally reflecting the increased duration of the green canopy, at average rates of 2.8 similar to t similar to ha-1 decade-1 for chitted seed (sprouted prior to planting) and 2.5 similar to t similar to ha-1 decade-1 for unchitted seed. The measured warming could contribute potential yield increases of up to 13.2 similar to t similar to ha-1 for chitted potato (range 7.119.3 similar to t similar to ha-1) and 11.5 similar to t similar to ha-1 for unchitted potato (range 7.115.5 similar to t similar to ha-1) equivalent to 3439% of the increased potential yield over the period or 2326% of the increase in actual measured yields.

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The objective of this work was to evaluate the feasibility of simulating maize yield in a sub‑tropical region of southern Brazil using the general large area model (Glam). A 16‑year time series of daily weather data were used. The model was adjusted and tested as an alternative for simulating maize yield at small and large spatial scales. Simulated and observed grain yields were highly correlated (r above 0.8; p<0.01) at large scales (greater than 100,000 km2), with variable and mostly lower correlations (r from 0.65 to 0.87; p<0.1) at small spatial scales (lower than 10,000 km2). Large area models can contribute to monitoring or forecasting regional patterns of variability in maize production in the region, providing a basis for agricultural decision making, and Glam‑Maize is one of the alternatives.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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