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1.
Many crop growth models require daily meteorological data. Consequently, model simulations can be obtained only at a limited number of locations, i.e. at weather stations with long-term records of daily data. To estimate the potential crop production at country level, we present in this study a geostatistical approach for spatial interpolation and aggregation of crop growth model outputs. As case study, we interpolated, simulated and aggregated crop growth model outputs of sorghum and millet in West-Africa. We used crop growth model outputs to calibrate a linear regression model using environmental covariates as predictors. The spatial regression residuals were investigated for spatial correlation. The linear regression model and the spatial correlation of residuals together were used to predict theoretical crop yield at all locations using kriging with external drift. A spatial standard deviation comes along with this prediction, indicating the uncertainty of the prediction. In combination with land use data and country borders, we summed the crop yield predictions to determine an area total. With spatial stochastic simulation, we estimated the uncertainty of that total production potential as well as the spatial cumulative distribution function. We compared our results with the prevailing agro-ecological Climate Zones approach used for spatial aggregation. Linear regression could explain up to 70% of the spatial variation of the yield. In three out of four cases the regression residuals showed spatial correlation. The potential crop production per country according to the Climate Zones approach was in all countries and cases except one within the 95% prediction interval as obtained after yield aggregation. We concluded that the geostatistical approach can estimate a country’s crop production, including a quantification of uncertainty. In addition, we stress the importance of the use of geostatistics to create tools for crop modelling scientists to explore relationships between yields and spatial environmental variables and to assist policy makers with tangible results on yield gaps at multiple levels of spatial aggregation. 相似文献
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基于高斯过程建模的物联网数据不确定性度量与预测 总被引:3,自引:0,他引:3
物联网已经成为农业大数据最重要的数据源之一,自动观测数据的质量控制对农业生产分析以及基础科研数据应用非常重要。针对农业物联网观测的一类非平稳时间序列数据中的数据缺失、野值剔除、感知故障预警和长时间预测等问题,采用光滑弱假设高斯先验,构建了基于高斯过程的自回归模型表征的动态系统,并通过样本集学习,形成能考虑噪声干扰的传感变化规律建模,并可提供预测误差带用于预测数据的不确定性度量。针对原始数据的缺失和野值问题,采用基于高斯过程的短期预测,可补齐缺失数据,利用其不确定性度量可甄别数据野值,进行野值剔除与替换,并在此基础上判断感知故障;给出了基于输入数据不确定性传播的多步迭代预测方法,使长期预测仍可以跟踪农业数据的动态轨迹,并可为其预测值提供不确定性度量;将温室采集的真实传感数据用于分析试验,验证了高斯过程用于服务器端的农业时间序列数据采集质量控制的可行性。 相似文献
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This work describes the analysis of the uncertainty linked to the annual direct and indirect losses of different nitrogenous compounds at the scale of a group of farms. The nitrogen (N) forms taken into account are: ammonia (NH3), nitric oxide (NO), nitrous oxide (N2O), dinitrogen (N2) and nitrate (NO3). The gaseous N emissions for the different components of the farms are estimated with a selection of adapted emission factors. The NO3 losses at the farm scale are calculated as the difference between the surplus of the farm-gate N balance and the gaseous N emissions. 相似文献
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指纹技术识别泥沙来源:不确定性研究进展 总被引:2,自引:0,他引:2
泥沙指纹技术是近年来研究流域泥沙来源与动态变化的一项重要技术方法,其主要局限性在于诸多的前提假设与实践条件的差异带入了一系列不确定性。泥沙从源到汇的迁移过程受自然环境和人为干扰的影响,其源地特征、迁移路径以及泥沙性质的潜在变化等均是指纹技术应用的不确定性因素,而采样方案设计、指纹选择方法、混合模型应用的一些主观因素进一步增加了不确定性的来源。不确定性分析是泥沙指纹技术的重要组成部分,是评估泥沙来源指纹识别结果可靠性的主要依据。本文综述了泥沙指纹技术的诸多不确定性问题以及主要应对方法的研究进展,总结了当前不确定性定量评估的研究现状并提出了未来的研究展望。 相似文献
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Florida ranks first in citrus production, with nearly 68% of all U.S. citrus growing in the season 2005-2006. Most of the citrus groves are located from central to south Florida, and agricultural irrigation permitting is regulated by three of Florida's five water management districts. Most of the permitting for citrus production in Highlands, Polk and Hillsborough counties is conducted by the Southwest Florida Water Management District (SWFWMD), and quantities are based on the District's AGMOD computer program. In 2003, the SWFWMD implemented new permit criteria so that permitted amounts were more representative of actual water use. This paper compares grower reported citrus irrigation water use in Highlands, Polk and Hillsborough counties from 1994 through 2005 with permitted and theoretical irrigation requirements calculated by a daily water balance. Two different sets of crop coefficients (Kc's) developed for citrus in Florida were compared in the daily soil water balance calculation of theoretical irrigation requirements. The percentage of irrigated area considered in this study ranged from 40 to 60% to simulate a range of grower practices. Meteorological data from two weather stations and additional rainfall information from 50 locations within the three counties was used in the water balance. Missing and error values in the meteorological historical record data were filled with weather generators. The multiannual average water consumption (including cold protection water use) from growers ranged from 243 (Hillsborough) to 406 mm (Highlands) and the multiannual average permitted irrigation requirement (without cold protection) ranged from 295 to 557 mm. The simulated gross irrigation requirements under different scenarios of location-Kc-wetted area were variable but mostly lower than the limits established by the district, except for some scenarios in Polk County, whose maximum simulated irrigation value reached 578 mm year−1. In general, permitted limits recommended by the SWFWMD seem to be reasonable for the actual water use by growers in these counties. 相似文献
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A hybrid fuzzy-stochastic water-management (FSWM) model is developed for agricultural sustainability under uncertainty, based on advancement of a multistage fuzzy-stochastic quadratic programming (MFSQP) approach. In MFSQP, uncertainties presented in terms of fuzziness and randomness can be incorporated within a multilayer scenario tree, such that revised decisions are permitted in each time period based on the realized values of the uncertain events. Moreover, fuzzy quadratic terms are used in the objective function to minimize the variation of satisfaction degrees among the constraints; it allows an increased flexibility in controlling the system risk in the optimization process. Results of the case study indicate that useful solutions for the planning of agricultural water management have been obtained. In the FSWM model, a number of policies for agricultural water supply are conducted. The results obtained can help decision makers to identify desired water-allocation schemes for agricultural sustainability under uncertainty, particularly when limited water resources are available for multiple competing users. 相似文献
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标准溶液的不确定度对农药残留检测起着非常重要的作用,影响着检测结果的准确性。笔者以实际应用的14种有机磷农药混合标准溶液为例,采用配制混合标准溶液过程单元操作的不确定度计算方法(top down),分析了在配制混合标准溶液过程中的所有影响因素,得到了最终的扩展不确定度。最终结果显示使用精准的移液器将储备液配置为混合标液,得到最终的扩展不确定度相对小。 相似文献