农作物种植条件下浅层地下水利用研究进展

农作物种植条件下浅层地下水利用的研究对于水资源的评价十分重要,关系到节水、农田合理灌溉和水资源科学管理。潜水蒸发的计算是浅层地下水利用研究中的一项非常重要的内容,系统总结了国内外潜水蒸发研究的现状,包括试验研究、经验公式总结和数值模拟模型的研究现状,并对其未来发展做了展望。     

彭曼公式在参考作物需水量中的应用

介绍几种作物需水量常用计算方法,并且利用彭曼公式计算甘肃省庆阳市巴家嘴灌区玉米的需水量,结果证明彭曼公式计算结果比以往的计算更为精确,从而为整个灌区的灌溉规划和管理提供了更为有利的依据。     

黄淮海平原作物灌溉需水与耕地生产潜力的耦合分析

对1991年和2000年气象数据进行空间插值,获得了黄淮海平原气象指标1km×1km空间网格数据,然后借助GIS数据处理与空间分析功能,通过计算参考蒸散量、作物需水量,估算了1991年和2000年黄淮海平原耕地作物灌溉需水量,并分析了其时空变化规律。利用农业生态地带模型(AEZ)计算了耕地生产潜力,通过对作物灌溉需水与耕地生产潜力的空间耦合分析,发现作物灌溉需水与耕地生产潜力之间呈线性正向相关,表明黄淮海平原灌溉需水满足程度是耕地生产潜力的一个制约因素。     

基因组学辅助作物改良研究进展

基因组学研究产生了功能分子标记和生物信息学等新型工具,并形成了能够提高作物改良效率和精确度的有关统计和遗传现象的新知识。基因组学研究对杂种优势和表观遗传学的解析及其操纵有巨大的潜力,最终可以了解一个群体中所有位点等位基因分离的相关知识,从而使育种家可以在微机上对基因型进行设计,并实施全基因组选择。当前高成本的实验限制了基因组学辅助的作物改良,自交作物和小作物尤其突出。然而,作物改良中的标记辅助选择育种将逐步进展到基因组学辅助育种。     

作物-害虫-天敌三级营养系统对臭氧增加的响应

综述了臭氧增加对作物-害虫-天敌三级营养系统影响的研究进展,探讨了其未来研究方向,旨在为未来害虫的生物防治提供科学依据和预警。     

Analysis of two variants of a spatially distributed crop model,using wavelet transforms and geostatistics

Models of crop yield are important for the assessment and optimization of agricultural systems. It is therefore necessary that crop models are suitably validated. In many circumstances, a model is required for prediction at a particular spatial scale (e.g. at a within-field scale for precision agriculture), and validation of the model should account for this. We compared spatially explicit methods to validate a grain yield model applied to a transect of 267 contiguous 0.72 × 0.72 m plots on an arable field at Silsoe, eastern England. Grain yield of wheat was determined in each plot during two growing seasons, and a crop model was used to predict the yield retrospectively. We used two variants of the model, each of which used different spatial variables as input. Observed and predicted yield were then compared with non-spatial statistics, but also with wavelet transforms (i.e. the adapted maximal overlap discrete wavelet transform) and geostatistics (i.e. a linear mixed model estimated by residual maximum likelihood). The latter two are spatially explicit statistical methods. The most successful of the variants required as input the daily evolution of leaf-area index in each plot. Validation of this variant with spatial statistics revealed that (i) the variance of the predictions tended to underestimate that of the observations, particularly at relatively coarse spatial scales, however, in relative terms, the distribution of observed variance across scales was described adequately by the model; (ii) the correlation of the predictions with the observations was weak at relatively fine scales but strong at relatively coarse scales; (iii) there was evidence that the correlation of the predictions with the observations was not uniform across the transect at relatively fine scales, which was possibly due to the underlying soil variation; and, (iv) the spatial pattern of model error suggested that some of the fine-scale yield variation, especially in the first growing season, could be attributed to soil compaction, a process not included in the model. These details were not apparent with non-spatial statistics; wavelets and geostatistics are therefore more appropriate tools for validating a spatially distributed crop model. We conclude that this variant of the model is therefore potentially useful for precision agriculture where we need to predict crop behaviour within small management zones, at the scale of tens of metres, but not to predict yield at finer scales. We outline how the most appropriate statistical technique for a particular study depends on whether the observations can be sampled regularly in space, whether we can assume the statistics are uniform across the landscape, the number of spatial scales of interest, and whether interpolation of the predictions, observations, and errors is required.     

Validating CERES-wheat under North-German environmental conditions

The predictive quality of CERES-wheat was tested under contrasting nitrogen management and temperate-maritime climate conditions of North-Germany. Field data from 9 years of observations were used in this study. The magnitudes of the genetic parameters of the local wheat cultivar “Orestis” were strongly influenced by seasonal weather fluctuations. For predicted yield and harvest biomass, the root mean square error was 2.2 t/ha and 3.2 t/ha, respectively. These errors were too large to permit a practical application of the CERES-wheat model for optimizing fertilizer management under the production conditions of North-Germany. The results of this study suggest that the model needs to be considerably improved with respect to the simulation of soil and plant water-relations, as well as the interaction between water and nitrogen uptake which were found to be inconsistent.     

Crop coefficients for winter wheat in a sub-humid climate regime

Estimations of evapotranspiration (ET) from natural surfaces are used in a large number of applications such as agricultural water management and water resources planning. Lack of reliable, cheap and easy-to-use instruments, associated with the chaotic and varying nature of the meteorological and plant physiological factors influencing ET cause these estimations to be based on calculated values rather than the measured ones. The two-step approach where ET from a reference crop is calculated and multiplied by empirical crop coefficients to obtain ET from a crop has gained wide acceptance. Daily coefficients for a winter wheat crop growing under standard conditions, i.e. not short of water and growing under optimal agronomic conditions, were estimated for a cold sub-humid climate regime. One of the two methods used to estimate ET from a reference crop required net radiation (R_n) as input. Two sets of coefficients were used for calculating R_n. Weather data from a meteorological station was used to estimate R_n and ET from the reference crop. The winter wheat ET was measured using an eddy covariance system during the main parts of the growing seasons 2004 and 2005. The meteorological data and field measurements were quality controlled and discarded from the analysis if flagged for errors. Daily values of ET from the reference crop and winter wheat calculated from hourly values were used to calculate the crop coefficients. Average daily crop coefficients were in the 1.1–1.15 range during mid-season with standard deviations ranging from 0.13 to 0.23 for both years. These values exceed values used in some sub-humid climate regime studies, but agree well with values from the international literature.     

Characterization of drought stress environments for upland rice and maize in central Brazil

Drought stresses arise when the combination of rainfall and soil water supply are insufficient to meet the transpiration needs of the crop. In the Cerrado region of Goiás state, Brazil, summer rainfall is typically greater than 1000 mm. However, drought stress can occur during rain-free periods of only 1–3 weeks, since roots are frequently restricted to shallow depths due to Al-induced acidity in deeper soil layers. If these droughts are frequent, then plant breeding programs need to consider how to develop suitable germplasm for the target population of environments (TPE). A crop simulation model was used to determine patterns of drought stress for 12 locations and >30 environments (6 years × 5–6 planting dates) for short and medium duration rice crops (planted in early summer), and for maize grown either as a 1st or 2nd crop in the summer cycle. Regression analysis of the simulations confirmed the greater yield impact in both crops of drought stress (quantified as the ratio of water-limited to potential transpiration) when it occurred around the time of flowering and early grain-filling. For rice, mild mid-season droughts occurred 40–60% of the time in virgin (0.4 m deep for rice or 0.5 m for maize) soils and improved (0.8 m for rice or 1.0 m for maize) soils, with a yield reduction of <30%. More severe reproductive and grain-filling stress (yield reductions of 50% for rice to 90% for maize) occurred less frequently in rice (<30% of time) and 1st maize crop (< 10% of time). The 2nd maize crop experienced the greatest proportion (75–90%) of drought stresses that reduced yield to <50% of potential, with most of these occasions associated with later planting. The rice breeding station (CNPAF) experiences the same pattern of different drought types as for the TPE, and is largely suitable for early-stage selection of adapted germplasm based on yield potential. However, selection for virgin soil types could be augmented by evaluation on some less-improved soils in the slightly drier parts of the TPE region. Similarly, the drought patterns at the maize research station (CNPMS) and the other maize screening locations are better suited to selection of lines for the improved soil types. Development of lines for the 2nd crop and on more virgin (acidic) soils would require more targeted selection at late planting dates in drier sites.     

新疆乌鲁木齐市复合绿地耗水特性研究

为了探明乌鲁木齐市典型的"草坪+白榆（Ulmus pumila L.）"复合绿地的耗水特性,在乌鲁木齐市红山公园,进行了定周期、变定额的灌溉试验,结果表明：在观测时段内复合绿地中草坪及榆树的日均耗水量均随灌水定额的增大而增大,且随生育期的推进整体呈现出先增大后减小的单峰曲线变化。各处理复合绿地主要生育期累积耗水量在668.5~996.4 mm之间变化,也随着灌水定额的增加而增大;复合绿地中草坪与榆树的耗水量之比在1：1~1：1.2之间变化,该比例随灌水定额的增大先增大后减小;各处理5-9月复合绿地的作物系数介于0.72~1.52之间,各处理主要生育期的作物系数均值随灌水定额的增加而增大;综合复合绿地的耗水及草坪生长情况,在降雨频率为75%的枯水年,乌鲁木齐市与试验区类似且养护水平相近的复合绿地较为适宜的喷灌灌水定额为36 mm,灌水周期为5~7 d。