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91.
M. Farooq N. Gogoi S. Barthakur B. Baroowa N. Bharadwaj S. S. Alghamdi K. H. M. Siddique 《Journal of Agronomy and Crop Science》2017,203(2):81-102
Water scarcity is a major constraint limiting grain legume production particularly in the arid and semi‐arid tropics. Different climate models have predicted changes in rainfall distribution and frequent drought spells for the future. Although drought impedes the productivity of grain legumes at all growth stages, its occurrence during reproductive and grain development stages (terminal drought) is more critical and usually results in significant loss in grain yield. However, the extent of yield loss depends on the duration and intensity of the stress. A reduction in the rate of net photosynthesis, and poor grain set and grain development are the principal reasons for terminal drought‐induced loss in grain yield. Insight into the impact and resistance mechanism of terminal drought is required for effective crop improvement programmes aiming to improve resistance to terminal drought in grain legumes. In this article, the impact of terminal drought on leaf development and senescence, light harvesting and carbon fixation, and grain development and grain composition is discussed. The mechanisms of resistance, management options, and innovative breeding and functional genomics strategies to improve resistance to terminal drought in grain legumes are also discussed. 相似文献
92.
不同林龄枫香子代性状变异与家系选择 总被引:5,自引:0,他引:5
对布设在安徽祁门县的首批84个枫香子代测定林,分析比较了9年生与3年生两个不同林龄胸径、树高性状的遗传力和遗传增益等参数,并开展了优良家系选择。结果表明不同时期入选的家系名称、数量及名次出现较大差异,大部分家系胸径、树高性状的家系遗传力、单株遗传力及遗传增益等参数估值,表现为随林龄增大而降低。研究结果为枫香良种选育的适宜林龄提供了参考依据。 相似文献
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95.
研究了均值-方差准则下,最优投资组合选择问题.投资者为了增加财富它可以在金融市场上投资.金融市场由一个无风险资产和n个带跳的风险资产组成,并假设金融市场具有马氏调制,买卖风险资产时,考虑交易费用.目标是,在终值财富的均值等于d的限制下,使终值财富的方差最小,即均值-方差组合选择问题.应用随机控制的理论解决该问题,获得了最优的投资策略和有效边界. 相似文献
96.
Landscape Zonation, benefit functions and target-based planning: Unifying reserve selection strategies 总被引:1,自引:0,他引:1
Atte Moilanen 《Biological conservation》2007,134(4):571-579
The most widespread reserve selection strategy is target-based planning, as specified under the framework of systematic conservation planning. Targets are given for the representation levels of biodiversity features, and site selection algorithms are employed to either meet the targets with least cost (the minimum set formulation) or to maximize the number of targets met with a given resource (maximum coverage). Benefit functions are another recent approach to reserve selection. In the benefit function framework the objective is to maximize the value of the reserve network, however value is defined. In one benefit function formulation value is a sum over species-specific values, and species-specific value is an increasing function of representation. This benefit function approach is computationally convenient, but because it allows free tradeoffs between species, it essentially makes the assumption that species are acting as surrogates, or samples from a larger regional species pool. The Zonation algorithm is a recent computational method that produces a hierarchy of conservation priority through the landscape. This hierarchy is produced via iterative removal of selection units (cells) using the criterion of least marginal loss of conservation value to decide which cell to remove next. The first variant of Zonation, here called core-area Zonation, has a characteristic of emphasizing core-areas of all species. Here I separate the Zonation meta-algorithm from the cell removal rule, the definition of marginal loss of conservation value utilized inside the algorithm. I show how additive benefit functions and target-based planning can be implemented into the Zonation framework via the use of particular kinds of cell removal rules. The core-area, additive benefit function and targeting benefit function variants of Zonation have interesting conceptual differences in how they treat and trade off between species in the planning process. 相似文献
97.
Ignacy Misztal Ignacio Aguilar Daniela Lourenco Li Ma Juan Pedro Steibel Miguel Toro 《Journal of animal science》2021,99(6)
Genomic selection (GS) is now practiced successfully across many species. However, many questions remain, such as long-term effects, estimations of genomic parameters, robustness of genome-wide association study (GWAS) with small and large datasets, and stability of genomic predictions. This study summarizes presentations from the authors at the 2020 American Society of Animal Science (ASAS) symposium. The focus of many studies until now is on linkage disequilibrium between two loci. Ignoring higher-level equilibrium may lead to phantom dominance and epistasis. The Bulmer effect leads to a reduction of the additive variance; however, the selection for increased recombination rate can release anew genetic variance. With genomic information, estimates of genetic parameters may be biased by genomic preselection, but costs of estimation can increase drastically due to the dense form of the genomic information. To make the computation of estimates feasible, genotypes could be retained only for the most important animals, and methods of estimation should use algorithms that can recognize dense blocks in sparse matrices. GWASs using small genomic datasets frequently find many marker-trait associations, whereas studies using much bigger datasets find only a few. Most of the current tools use very simple models for GWAS, possibly causing artifacts. These models are adequate for large datasets where pseudo-phenotypes such as deregressed proofs indirectly account for important effects for traits of interest. Artifacts arising in GWAS with small datasets can be minimized by using data from all animals (whether genotyped or not), realistic models, and methods that account for population structure. Recent developments permit the computation of P-values from genomic best linear unbiased prediction (GBLUP), where models can be arbitrarily complex but restricted to genotyped animals only, and single-step GBLUP that also uses phenotypes from ungenotyped animals. Stability was an important part of nongenomic evaluations, where genetic predictions were stable in the absence of new data even with low prediction accuracies. Unfortunately, genomic evaluations for such animals change because all animals with genotypes are connected. A top-ranked animal can easily drop in the next evaluation, causing a crisis of confidence in genomic evaluations. While correlations between consecutive genomic evaluations are high, outliers can have differences as high as 1 SD. A solution to fluctuating genomic evaluations is to base selection decisions on groups of animals. Although many issues in GS have been solved, many new issues that require additional research continue to surface. 相似文献
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99.
旨在探究快速型黄羽肉鸡饲料利用效率性状的遗传参数,评估不同方法所得估计育种值的准确性。本研究以自主培育的快速型黄羽肉鸡E系1 923个个体(其中公鸡1 199只,母鸡724只)为研究素材,采用"京芯一号"鸡55K SNP芯片进行基因分型。分别利用传统最佳线性无偏预测(BLUP)、基因组最佳线性无偏预测(GBLUP)和一步法(SSGBLUP)3种方法,基于加性效应模型进行遗传参数估计,通过10倍交叉验证比较3种方法所得估计育种值的准确性。研究性状包括4个生长性状和4个饲料利用效率性状:42日龄体重(BW42D)、56日龄体重(BW56D)、日均增重(ADG)、日均采食量(ADFI)和饲料转化率(FCR)、剩余采食量(RFI)、剩余增长体重(RG)、剩余采食和增长体重(RIG)。结果显示,4个饲料利用效率性状均为低遗传力(0.08~0.20),其他生长性状为中等偏低遗传力(0.11~0.35);4个饲料利用效率性状间均为高度遗传相关,RFI、RIG与ADFI间为中度遗传相关,RFI与ADG间无显著相关性,RIG与ADG间为低度遗传相关。本研究在获得SSGBLUP方法的最佳基因型和系谱矩阵权重比基础上,比较8个性状的估计育种值准确性,SSGBLUP方法获得的准确性分别比传统BLUP和GBLUP方法提高3.85%~14.43%和5.21%~17.89%。综上,以RIG为选择指标能够在降低日均采食量的同时保持日均增重,比RFI更适合快速型黄羽肉鸡的选育目标;采用最佳权重比进行SSGBLUP分析,对目标性状估计育种值的预测性能最优,建议作为快速型黄羽肉鸡基因组选择方法。 相似文献
100.
旨在提出一种新型基因组关系矩阵并验证其在多品种联合群体中的模拟应用效果。本研究利用QMsim软件模拟牛的表型数据和基因型数据;利用Gmatrix软件构建常规G阵;利用R语言构建新型G阵,新型G阵在常规G阵的基础上,将多品种联合群体的非哈代-温伯格平衡位点考虑在内;利用DMU软件使用“一步”法模型计算基因组估计育种值(estimated genomic breeding value,GEBV);比较不同情况下使用两种G阵的GEBV预测准确性。结果表明,在不同遗传力及QTL数下,不对新型G阵使用A22阵加权就能达到常规G阵使用A22阵加权时的GEBV预测准确性。在系谱部分缺失时,新型G阵不加权较常规G阵加权时GEBV预测准确性高。证明,在系谱有部分缺失时,新型G阵对多品种GEBV的预测有一定优势。 相似文献