994 resultados para Crop yield forecasting


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Crop production is inherently sensitive to fluctuations in weather and climate and is expected to be impacted by climate change. To understand how this impact may vary across the globe many studies have been conducted to determine the change in yield of several crops to expected changes in climate. Changes in climate are typically derived from a single to no more than a few General Circulation Models (GCMs). This study examines the uncertainty introduced to a crop impact assessment when 14 GCMs are used to determine future climate. The General Large Area Model for annual crops (GLAM) was applied over a global domain to simulate the productivity of soybean and spring wheat under baseline climate conditions and under climate conditions consistent with the 2050s under the A1B SRES emissions scenario as simulated by 14 GCMs. Baseline yield simulations were evaluated against global country-level yield statistics to determine the model's ability to capture observed variability in production. The impact of climate change varied between crops, regions, and by GCM. The spread in yield projections due to GCM varied between no change and a reduction of 50%. Without adaptation yield response was linearly related to the magnitude of local temperature change. Therefore, impacts were greatest for countries at northernmost latitudes where warming is predicted to be greatest. However, these countries also exhibited the greatest potential for adaptation to offset yield losses by shifting the crop growing season to a cooler part of the year and/or switching crop variety to take advantage of an extended growing season. The relative magnitude of impacts as simulated by each GCM was not consistent across countries and between crops. It is important, therefore, for crop impact assessments to fully account for GCM uncertainty in estimating future climates and to be explicit about assumptions regarding adaptation.

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In the recent past there was a widespread working assumption in many countries that problems of food production had been solved, and that food security was largely a matter of distribution and access to be achieved principally by open markets. The events of 2008 challenged these assumptions, and made public a much wider debate about the costs of current food production practices to the environment and whether these could be sustained. As in the past 50 years, it is anticipated that future increases in crop production will be achieved largely by increasing yields per unit area rather than by increasing the area of cropped land. However, as yields have increased, so the ratio of photosynthetic energy captured to energy expended in crop production has decreased. This poses a considerable challenge: how to increase yield while simultaneously reducing energy consumption (allied to greenhouse gas emissions) and utilizing resources such as water and phosphate more efficiently. Given the timeframe in which the increased production has to be realized, most of the increase will need to come from crop genotypes that are being bred now, together with known agronomic and management practices that are currently under-developed.

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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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There is concern that modern cultivars and/or agronomic practices have resulted in reduced concentrations of mineral elements essential to human nutrition in edible crops. Increased yields are often associated with reduced concentrations of mineral elements in produce, and a number of recent studies have indicated that, when grown under identical conditions, the concentrations of several mineral elements are lower in genotypes yielding more grain or shoot biomass than in older, lower-yielding genotypes. Potato is a significant crop, grown worldwide, yet few studies have investigated whether increasing yields, through agronomy or breeding, affects the concentrations of mineral elements in tubers. This article examines the hypothesis that increasing yields, either by the application of mineral fertilizers and/or by growing higher-yielding varieties, leads to decreased concentrations of mineral elements in tubers. It reports that the application of fertilizers influences tuber elemental composition in a complex manner, presumably as a consequence of soil chemistry and interactions between mineral elements within the plant, that considerable variation exists between potato genotypes in the concentrations of mineral elements in their tubers, and that, like in other crops, higher-yielding genotypes occasionally have lower concentrations of some mineral elements in their edible tissues than lower-yielding genotypes.

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Research has highlighted the usefulness of the Gilt–Equity Yield Ratio (GEYR) as a predictor of UK stock returns. This paper extends recent studies by endogenising the threshold at which the GEYR switches from being low to being high or vice versa, thus improving the arbitrary nature of the determination of the threshold employed in the extant literature. It is observed that a decision rule for investing in equities or bonds, based on the forecasts from a regime switching model, yields higher average returns with lower variability than a static portfolio containing any combinations of equities and bonds. A closer inspection of the results reveals that the model has power to forecast when investors should steer clear of equities, although the trading profits generated are insufficient to outweigh the associated transaction costs.

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The role of ethylene in regulating organ senescence in Arabidopsis has been investigated by studying the development of mutants that have an attenu- ated capacity to perceive the gas. The onset of leaf senescence and floral organ abscission was delayed in the ethylene-insensitive mutant etr1. The photosynthetic life span of rosette leaves was similarly extended in the gain- of-function mutant ers2, and this mutant also exhibited a delay in the timing of pod dehiscence primarily as a con- sequence of an extension in the final stages of senescence. A detailed analysis of yield revealed that whilst thousand grain weight was increased, by as much as 20 %, in etr1, ein4, and the loss-of-function mutant etr2, only the latter showed a significant increase in total weight of seeds produced per plant. The other studied mutants exhibited a reduction in total seed yield of almost 40 %. These observations are discussed in the context of the possible role of ethylene in regulating organ senescence and their significance in the breeding of crop plants with enhanced phenotypic characteristics.

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The relationship between food security and sustainable land use is considered to be of the uttermost importance to increase yields without having to increase the agricultural land area over which crops are grown. In the present study nitrogen concentration (25 and 85 kg ha-1) and planting density (6.7, 10 and 25 plants m-2) were investigated for their effect on whole plant physiology and pod seed yield in kale (Brassica oleracea), to determine if the fruit (pod) yield could be manipulated agronomically. Nitrogen concentration did not significantly affect seed yield and it is therefore recommended that the lower concentration be used commercially. Conversely planting density did have a significant effect with increases in seed yield observed at the highest planting density of 25 plants m-2, therefore this high planting density would be recommended commercially to maximise area efficiency, highlighting that simple agronomic changes are capable of increasing crop yields over a set area.

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Break crops and multi-crop rotations are common in arable farm management, and the soil quality inherited from a previous crop is one of the parameters that determine the gross margin that is achieved with a given crop from a given parcel of land. In previous work we developed a dynamic economic model to calculate the potential yield and gross margin of a set of crops grown in a selection of typical rotation scenarios, and we reported use of the model to calculate coexistence costs for GM maize grown in a crop rotation. The model predicts economic effects of pest and weed pressures in monthly time steps. Validation of the model in respect of specific traits is proceeding as data from trials with novel crop varieties is published. Alongside this aspect of the validation process, we are able to incorporate data representing the economic impact of abiotic stresses on conventional crops, and then use the model to predict the cumulative gross margin achievable from a sequence of conventional crops grown at varying levels of abiotic stress. We report new progress with this aspect of model validation. In this paper, we report the further development of the model to take account of abiotic stress arising from drought, flood, heat or frost; such stresses being introduced in addition to variable pest and weed pressure. The main purpose is to assess the economic incentive for arable farmers to adopt novel crop varieties having multiple ‘stacked’ traits introduced by means of various biotechnological tools available to crop breeders.

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Annual losses of cocoa in Ghana to mirids are significant. Therefore, accurate timing of insecticide application is critical to enhance yields. However, cocoa farmers often lack information on the expected mirid population for each season to enable them to optimise pesticide use. This study assessed farmers’ knowledge and perceptions of mirid control and their willingness to use forecasting systems informing them of expected mirid peaks and time of application of pesticides. A total of 280 farmers were interviewed in the Eastern and Ashanti regions of Ghana with a structured open and closed ended questionnaire. Most farmers (87%) considered mirids as the most important insect pest on cocoa with 47% of them attributing 30-40% annual crop loss to mirid damage. There was wide variation in the timing of insecticide application as a result of farmers using different sources of information to guide the start of application. The majority of farmers (56%) do not have access to information on the type, frequency and timing of insecticides to use. However, respondents who are members of farmer groups had better access to such information. Extension officers were the preferred channel for information transfer to farmers with 72% of farmers preferring them to other available methods of communication. Almost all the respondents (99%) saw the need for a comprehensive forecasting system to help farmers manage cocoa mirids. The importance of accurate timing for mirid control based on forecasted information to farmer groups and extension officers was discussed.

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Global food security, particularly crop fertilization and yield production, is threatened by heat waves that are projected to increase in frequency and magnitude with climate change. Effects of heat stress on the fertilization of insect-pollinated plants are not well understood, but experiments conducted primarily in self-pollinated crops, such as wheat, show that transfer of fertile pollen may recover yield following stress. We hypothesized that in the partially pollinator-dependent crop, faba bean (Vicia faba L.), insect pollination would elicit similar yield recovery following heat stress. We exposed potted faba bean plants to heat stress for 5 days during floral development and anthesis. Temperature treatments were representative of heat waves projected in the UK for the period 2021-2050 and onwards. Following temperature treatments, plants were distributed in flight cages and either pollinated by domesticated Bombus terrestris colonies or received no insect pollination. Yield loss due to heat stress at 30°C was greater in plants excluded from pollinators (15%) compared to those with bumblebee pollination (2.5%). Thus, the pollinator dependency of faba bean yield was 16% at control temperatures (18 to 26°C) and extreme stress (34°C), but was 53% following intermediate heat stress at 30°C. These findings provide the first evidence that the pollinator dependency of crops can be modified by heat stress, and suggest that insect pollination may become more important in crop production as the probability of heat waves increases.

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Organic fertilizers based on seaweed extract potentially have beneficial effects on many crop plants. Herewe investigate the impact of organic fertilizer on Rosmarinus officinalis measured by both yield and oilquality. Plants grown in a temperature-controlled greenhouse with a natural photoperiod and a controlledirrigation system were treated with seaweed fertilizer and an inorganic fertilizer of matching mineralcomposition but with no organic content. Treatments were either by spraying on to the foliage or wateringdirect to the compost. The essential oil was extracted by hydro-distillation with a Clevenger apparatusand analysed by gas-chromatography mass-spectrometry (GC–MS) and NMR. The chemical composi-tions of the plants were compared, and qualitative differences were found between fertilizer treatmentsand application methods. Thus sprayed seaweed fertilizer showed a significantly higher percentage of�-pinene, �-phellandrene, �-terpinene (monoterpenes) and 3-methylenecycloheptene than other treat-ments. Italicene, �-bisabolol (sesquiterpenes), �-thujene, and E-isocitral (monoterpenes) occurred insignificantly higher percentages for plants watered with the seaweed extract. Each was significantly dif-ferent to the inorganic fertilizer and to controls. The seaweed treatments caused a significant increasein oil amount and leaf area as compared with both inorganic treatments and the control regardless ofapplication method.

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Background and Aims Root traits can be selected for crop improvement. Techniques such as soil excavations can be used to screen root traits in the field, but are limited to genotypes that are well-adapted to field conditions. The aim of this study was to compare a low-cost, high-throughput root phenotyping (HTP) technique in a controlled environment with field performance, using oilseed rape (OSR; Brassica napus) varieties. Methods Primary root length (PRL), lateral root length and lateral root density (LRD) were measured on 14-d-old seedlings of elite OSR varieties (n = 32) using a ‘pouch and wick’ HTP system (∼40 replicates). Six field experiments were conducted using the same varieties at two UK sites each year for 3 years. Plants were excavated at the 6- to 8-leaf stage for general vigour assessments of roots and shoots in all six experiments, and final seed yield was determined. Leaves were sampled for mineral composition from one of the field experiments. Key Results Seedling PRL in the HTP system correlated with seed yield in four out of six (r = 0·50, 0·50, 0·33, 0·49; P < 0·05) and with emergence in three out of five (r = 0·59, 0·22, 0·49; P < 0·05) field experiments. Seedling LRD correlated positively with leaf concentrations of some minerals, e.g. calcium (r = 0·46; P < 0·01) and zinc (r = 0·58; P < 0·001), but did not correlate with emergence, general early vigour or yield in the field. Conclusions Associations between PRL and field performance are generally related to early vigour. These root traits might therefore be of limited additional selection value, given that vigour can be measured easily on shoots/canopies. In contrast, LRD cannot be assessed easily in the field and, if LRD can improve nutrient uptake, then it may be possible to use HTP systems to screen this trait in both elite and more genetically diverse, non-field-adapted OSR.

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With the aim of determining the genetic basis of metabolic regulation in tomato fruit, we constructed a detailed physical map of genomic regions spanning previously described metabolic quantitative trait loci of a Solanum pennellii introgression line population. Two genomic libraries from S. pennellii were screened with 104 colocated markers from five selected genomic regions, and a total of 614 bacterial artificial chromosome (BAC)/cosmids were identified as seed clones. Integration of sequence data with the genetic and physical maps of Solanum lycopersicum facilitated the anchoring of 374 of these BAC/cosmid clones. The analysis of this information resulted in a genome-wide map of a nondomesticated plant species and covers 10% of the physical distance of the selected regions corresponding to approximately 1% of the wild tomato genome. Comparative analyses revealed that S. pennellii and domesticated tomato genomes can be considered as largely colinear. A total of 1,238,705 bp from both BAC/cosmid ends and nine large insert clones were sequenced, annotated, and functionally categorized. The sequence data allowed the evaluation of the level of polymorphism between the wild and cultivated tomato species. An exhaustive microsynteny analysis allowed us to estimate the divergence date of S. pennellii and S. lycopersicum at 2.7 million years ago. The combined results serve as a reference for comparative studies both at the macrosyntenic and microsyntenic levels. They also provide a valuable tool for fine-mapping of quantitative trait loci in tomato. Furthermore, they will contribute to a deeper understanding of the regulatory factors underpinning metabolism and hence defining crop chemical composition.

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Parametric term structure models have been successfully applied to innumerous problems in fixed income markets, including pricing, hedging, managing risk, as well as studying monetary policy implications. On their turn, dynamic term structure models, equipped with stronger economic structure, have been mainly adopted to price derivatives and explain empirical stylized facts. In this paper, we combine flavors of those two classes of models to test if no-arbitrage affects forecasting. We construct cross section (allowing arbitrages) and arbitrage-free versions of a parametric polynomial model to analyze how well they predict out-of-sample interest rates. Based on U.S. Treasury yield data, we find that no-arbitrage restrictions significantly improve forecasts. Arbitrage-free versions achieve overall smaller biases and Root Mean Square Errors for most maturities and forecasting horizons. Furthermore, a decomposition of forecasts into forward-rates and holding return premia indicates that the superior performance of no-arbitrage versions is due to a better identification of bond risk premium.

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