970 resultados para Agronomy and Crop Science


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The identification and characterization of differential gene expression from tissues subjected to stress has gained much attention in plant research. The recognition of elements involved in the response to a particular stress enhances the possibility of promoting crop improvement through direct genetic modification. However, the performance of some of the 'first generation' of transgenic plants with the incorporation of a single gene has not always been as expected. These results have stimulated the development of new transgenic constructions introducing more than one gene and capable of modifying complex pathways. Several techniques are available to conduct the analysis of gene regulation, with such information providing the basis for novel constructs specifically designed to modify metabolism. This review deals with techniques that allow the identification and characterization of differentially-expressed genes and the use of molecular pathway information to produce transgenic plants.

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A methodology is presented for the development of a combined seasonal weather and crop productivity forecasting system. The first stage of the methodology is the determination of the spatial scale(s) on which the system could operate; this determination has been made for the case of groundnut production in India. Rainfall is a dominant climatic determinant of groundnut yield in India. The relationship between yield and rainfall has been explored using data from 1966 to 1995. On the all-India scale, seasonal rainfall explains 52% of the variance in yield. On the subdivisional scale, correlations vary between variance r(2) = 0.62 (significance level p < 10(-4)) and a negative correlation with r(2) = 0.1 (p = 0.13). The spatial structure of the relationship between rainfall and groundnut yield has been explored using empirical orthogonal function (EOF) analysis. A coherent, large-scale pattern emerges for both rainfall and yield. On the subdivisional scale (similar to 300 km), the first principal component (PC) of rainfall is correlated well with the first PC of yield (r(2) = 0.53, p < 10(-4)), demonstrating that the large-scale patterns picked out by the EOFs are related. The physical significance of this result is demonstrated. Use of larger averaging areas for the EOF analysis resulted in lower and (over time) less robust correlations. Because of this loss of detail when using larger spatial scales, the subdivisional scale is suggested as an upper limit on the spatial scale for the proposed forecasting system. Further, district-level EOFs of the yield data demonstrate the validity of upscaling these data to the subdivisional scale. Similar patterns have been produced using data on both of these scales, and the first PCs are very highly correlated (r(2) = 0.96). Hence, a working spatial scale has been identified, typical of that used in seasonal weather forecasting, that can form the basis of crop modeling work for the case of groundnut production in India. Last, the change in correlation between yield and seasonal rainfall during the study period has been examined using seasonal totals and monthly EOFs. A further link between yield and subseasonal variability is demonstrated via analysis of dynamical data.

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Runoff, sediment, total phosphorus and total dissolved phosphorus losses in overland flow were measured for two years on unbounded plots cropped with wheat and oats. Half of the field was cultivated with minimum tillage (shallow tillage with a tine cultivator) and half was conventionally ploughed. Within each cultivation treatment there were different treatment areas (TAs). In the first year of the experiment, one TA was cultivated up and down the slope, one TA was cultivated on the contour, with a beetle bank acting as a vegetative barrier partway up the slope, and one had a mixed direction cultivation treatment, with cultivation and drilling conducted up and down the slope and all subsequent operations conducted on the contour. In the second year, this mixed treatment was replaced with contour cultivation. Results showed no significant reduction in runoff, sediment losses or total phosphorus losses from minimum tillage when compared to the conventional plough treatment, but there were increased losses of total dissolved phosphorus with minimum tillage. The mixed direction cultivation treatment increased surface runoff and losses of sediment and phosphorus. Increasing surface roughness with contour cultivation reduced surface runoff compared to up and down slope cultivation in both the plough and minimum tillage treatment areas, but this trend was not significant. Sediment and phosphorus losses in the contour cultivation treatment followed a very similar pattern to runoff. Combining contour cultivation with a vegetative barrier in the form of a beetle bank to reduce slope length resulted in a non-significant reduction in surface runoff, sediment and total phosphorus when compared to up and down slope cultivation, but there was a clear trend towards reduced losses. However, the addition of a beetle bank did not provide a significant reduction in runoff, sediment losses or total phosphorus losses when compared to contour cultivation, suggesting only a marginal additional benefit. The economic implications for farmers of the different treatment options are investigated in order to assess their suitability for implementation at a field scale.

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In this study was analyzed the effect of crop year and harvesting time on the fatty acid composition of cv. Picual virgin olive oil. The study was carried out during the fruit ripening period for three crop seasons. The mean fatty acid composition of Picual oils was determined. The oils contained palmitic acid (11.9%), oleic acid (79.3%), and linoleic acid (2.95%). The content of palmitic acid and saturated fatty acids decreased during fruit ripening while oleic and linoleic acids increased. The amount of stearic and linolenic acids decreased. The amount of saturated acids, palmitic and stearic, and the polyunsaturated acids linoleic and linolenic was dependent on the time of harvest, whereas the amount of oleic acid varied with the crop year. The differences observed between crop years for both palmitic and linoleic acid may be explained by the differences in the temperature during oil biosynthesis and by the amount of summer rainfall for oleic acid content. A significant relationship was observed between the MUFA/PUFA ratio and the oxidative stability measured by the Rancimat method.

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Season-long monitoring of on-farm rice (Oryza sativa, L.) plots in Nepal explored farmers' decision-making process on the deployment of varieties to agroecosystems, application of production inputs to varieties, agronomic practices and relationship between economic return and area planted per variety. Farmers deploy varieties [landraces (LRs) and modern varieties (MVs)] to agroecosystems based on their understanding of characteristics of varieties and agroecosystems, and the interaction between them. In marginal growing conditions, LRs can compete with MVs. Within an agroecosystem, economic return and area planted to varieties have positive relationship, but this is not so between agroecosystems. LRs are very diverse on agronomic and economic traits; therefore, they cannot be rejected a priori as inferior materials without proper evaluation. LRs have to be evaluated for useful traits and utilized in breeding programmes to generate farmer-preferred materials for marginal environments and for their conservation on-farm.

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Although the ‘chronicle of chronicles’ compiled at Worcester c1095-c1140 is now firmly attributed to John of Worcester, rather than Florence, major questions remain. A central issue is that the semi-autograph manuscript of the chronicle (now Oxford, Corpus Christi College, Ms 157) underwent several alterations to its structure and contents, as codicological evidence demonstrates. These included the incorporation of important illuminations, which have been surprisingly little considered in their overall manuscript context. This article focuses on these illuminations, and will argue that their presence in this version of the chronicle makes it something even more distinctive than the learned, revisionist chronological work of Marianus Scotus upon which it was based. John of Worcester’s chosen images are linked not only to his political narrative but also to theological works and to cutting-edge science, newly translated from Arabic. The presence of such miniatures in a twelfth-century chronicle is unique, and they are central to the final form given to the Worcester chronicle by John of Worcester himself in this key manuscript. Their analysis thus brings into focus the impressive assembly of materials which the chronicle offered to readers, to shape their understanding of ongoing events.

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Developing models to predict the effects of social and economic change on agricultural landscapes is an important challenge. Model development often involves making decisions about which aspects of the system require detailed description and which are reasonably insensitive to the assumptions. However, important components of the system are often left out because parameter estimates are unavailable. In particular, measurements of the relative influence of different objectives, such as risk, environmental management, on farmer decision making, have proven difficult to quantify. We describe a model that can make predictions of land use on the basis of profit alone or with the inclusion of explicit additional objectives. Importantly, our model is specifically designed to use parameter estimates for additional objectives obtained via farmer interviews. By statistically comparing the outputs of this model with a large farm-level land-use data set, we show that cropping patterns in the United Kingdom contain a significant contribution from farmer’s preference for objectives other than profit. In particular, we found that risk aversion had an effect on the accuracy of model predictions, whereas preference for a particular number of crops grown was less important. While nonprofit objectives have frequently been identified as factors in farmers’ decision making, our results take this analysis further by demonstrating the relationship between these preferences and actual cropping patterns.

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There is little consensus on how agriculture will meet future food demands sustainably. Soils and their biota play a crucial role by mediating ecosystem services that support agricultural productivity. However, a multitude of site-specific environmental factors and management practices interact to affect the ability of soil biota to perform vital functions, confounding the interpretation of results from experimental approaches. Insights can be gained through models, which integrate the physiological, biological and ecological mechanisms underpinning soil functions. We present a powerful modelling approach for predicting how agricultural management practices (pesticide applications and tillage) affect soil functioning through earthworm populations. By combining energy budgets and individual-based simulation models, and integrating key behavioural and ecological drivers, we accurately predict population responses to pesticide applications in different climatic conditions. We use the model to analyse the ecological consequences of different weed management practices. Our results demonstrate that an important link between agricultural management (herbicide applications and zero, reduced and conventional tillage) and earthworms is the maintenance of soil organic matter (SOM). We show how zero and reduced tillage practices can increase crop yields while preserving natural ecosystem functions. This demonstrates how management practices which aim to sustain agricultural productivity should account for their effects on earthworm populations, as their proliferation stimulates agricultural productivity. Synthesis and applications. Our results indicate that conventional tillage practices have longer term effects on soil biota than pesticide control, if the pesticide has a short dissipation time. The risk of earthworm populations becoming exposed to toxic pesticides will be reduced under dry soil conditions. Similarly, an increase in soil organic matter could increase the recovery rate of earthworm populations. However, effects are not necessarily additive and the impact of different management practices on earthworms depends on their timing and the prevailing environmental conditions. Our model can be used to determine which combinations of crop management practices and climatic conditions pose least overall risk to earthworm populations. Linking our model mechanistically to crop yield models would aid the optimization of crop management systems by exploring the trade-off between different ecosystem services.