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1.
近60年河北省冬小麦干旱风险时空规律 总被引：2，自引：0，他引：2
干旱是造成作物减产的主要自然灾害,开展作物干旱成因机制和时空特征研究,对于稳定区域粮食生产有重要意义。本研究基于河北省内18个国家标准气象站点1958—2016年的长时间序列观测资料,采用水分亏缺指数(CWDI)作为干旱评价指标,分析了近60年来河北省冬小麦的干旱风险时空格局;通过CWDI对不同气象因子的敏感性分析,进一步探究了冬小麦干旱的成因机制。研究表明,冬小麦生育期需水量和干旱风险呈先增后减再增加的特征,在拔节–抽穗阶段的干旱风险最高,其次是抽穗-成熟阶段。冬小麦全生育期间干旱等级以重旱和特旱为主,特别在其产量形成的关键生长中后期,河北省东南部黑龙港地区面临较高的旱灾风险。冬小麦干旱受降水、气温、湿度等多种因素的影响,其中影响最大的是降水;气温是影响冬小麦生育后期干旱程度的关键因子,伴随近几十年气候变化冬小麦生长期内温度明显升高,将增加冬小麦生长期的耗水量和灌溉需求。本研究揭示了气候变化影响下河北省冬小麦干旱风险的时空演变规律,识别出了干旱灾害的高风险区和关键生育期阶段,可为优化冬小麦灌溉管理和农田防灾减灾提供参考依据。 相似文献
2.
B. Basso D. Cammarano D. Chen G. Cafiero M. Amato G. Bitella R. Rossi & F. Basso 《Journal of Agronomy and Crop Science》2009,195(4):301-312
Wheat yield and protein content are spatially variable because of inherent spatial variability of factors affecting the yield at field scale. In Mediterranean environments, yield variability is often caused by the irregular weather pattern, particularly rainfall and by position on the landscape. The objective of this study was to determine the effects of landscape position and rainfall on spatial variability of wheat yield and protein in a rolling terrain field of Southern Italy, and to propose stable management areas through simulation modelling and georesistivity imaging in rolling landscape. The study was carried out in Southern Italy, during 2 years of wheat monoculture; extensive soil properties and in-season plant measurements were measured. This study showed that soil water content was the main factor affecting spatial variation of yield for both years. The interactions between rainfall, topography and soil attributes increase the chances to observe yield variability among years. The principal component analysis demonstrated that for both years, soil water content explained most of the variability. The crop simulation model provided excellent results when compared with measured data with root mean square error of 0.2 t ha−1 . The simulated cumulative probability function showed that the model was able to confirm the yield temporal stability of three different zones. 相似文献
3.
The crop growth is highly dependent on growth conditions which vary from year to year making precision farming challenging. In the present paper was first investigated whether varying soil physical properties reflect the within-field yield variation of small grain cereals and how do the variations in weather conditions between growing seasons affect the within-field yield variation. Secondly, the potential biomass accumulation of the crop in existing soil and weather conditions was simulated. The simulated and experimentally based site-specific total biomasses were compared in order to find out whether the soil data explains the observed variations in yield.Three experimental fields size of 3–4 ha were established to examine the spatio-temporal yield variation during three years. The clay content of soils was high (> 46%) and soils were classified as Stagni-Vertic Cambisols. Correlations between soil water retention properties and crop yield were studied. Top and subsoil saturated (SWC), field capacity (FC) and permanent wilting point (PWP) water content, and saturated hydraulic conductivity of soil (Ksat), were determined from 19 to 24 places on each field once during the three years experimental period. During growing seasons, soil moisture content and leaf area index (LAI) were determined at same places biweekly, and yield was harvested. Spring barley (Hordeum vulgare) was grown on two fields, and spring wheat (Triticum aestivum, 2 years) and spring oilseed rape (Brassica napus L., one year) were grown on the third field.The measured grain yields correlated with selected soil physical properties only in few cases. The observed spatial variation in the biomass was in most cases found to be higher than the simulated. Therefore, the above mentioned parameters were not enough to predict the yield correctly in case of high variations. There were other factors decreasing the observed yield e.g. lodging, cold summer, extremely high precipitation and slopes in field. According to our results it is evident that it is very difficult to predict site-specific biomass accumulation solely by soil properties in order, for instance, to fertilize in a site-specific manner. Therefore one needs to measure the crop during the growing season in order to simulate the biomass accumulation for precision farming purposes. 相似文献
4.
《European Journal of Agronomy》2007,26(2):82-91
The identification of homogeneous management zones within a field is crucial for variable rate application of agronomic inputs. This study proposed a methodology to identify homogeneous management zones within a 8 ha field, based on the stability of measured and simulated yield patterns in a maize–soybean–wheat crop rotation in north-east Italy. Crop growth and yield were simulated over a 14-year period (1989–2002) using CERES-Maize, CROPGRO-Soybean and CERES-Wheat models to account for weather effects on yield spatial patterns. The overlay of long-term assessments of yield spatial and temporal data allowed for the identification of two stable zones with different yield levels, one with greater yield (called HS for high and stable yield) and one with lower yield (called LS for low and stable yield). The size of the HS zone identified using 14 years of simulated yield was smaller than the one obtained when considering only yield monitor data taken during the 5-year crop rotation. The LS zone was larger when using simulated data, confirming that the consistency of temporal stability increased by increasing the years considered. The models were able to closely simulate yield across the field when site-specific inputs were used, showing potential for use in yield map interpretation in the context of precision agriculture. Results showed that a combination of GIS tools and crop growth simulation models can be used to identify temporally stable zones, which is a fundamental prerequisite for adopting variable rate technologies. 相似文献
5.
The aggregation of simulated gridded crop yields to national or regional scale requires information on temporal and spatial patterns of crop-specific harvested areas. This analysis estimates the uncertainty of simulated gridded yield time series related to the aggregation with four different harvested area data sets. We compare aggregated yield time series from the Global Gridded Crop Model Intercomparison project for four crop types from 14 models at global, national, and regional scale to determine aggregation-driven differences in mean yields and temporal patterns as measures of uncertainty.The quantity and spatial patterns of harvested areas differ for individual crops among the four data sets applied for the aggregation. Also simulated spatial yield patterns differ among the 14 models. These differences in harvested areas and simulated yield patterns lead to differences in aggregated productivity estimates, both in mean yield and in the temporal dynamics.Among the four investigated crops, wheat yield (17% relative difference) is most affected by the uncertainty introduced by the aggregation at the global scale. The correlation of temporal patterns of global aggregated yield time series can be as low as for soybean (r = 0.28).For the majority of countries, mean relative differences of nationally aggregated yields account for 10% or less. The spatial and temporal difference can be substantial higher for individual countries. Of the top-10 crop producers, aggregated national multi-annual mean relative difference of yields can be up to 67% (maize, South Africa), 43% (wheat, Pakistan), 51% (rice, Japan), and 427% (soybean, Bolivia). Correlations of differently aggregated yield time series can be as low as r = 0.56 (maize, India), r = 0.05 (wheat, Russia), r = 0.13 (rice, Vietnam), and r = −0.01 (soybean, Uruguay). The aggregation to sub-national scale in comparison to country scale shows that spatial uncertainties can cancel out in countries with large harvested areas per crop type. We conclude that the aggregation uncertainty can be substantial for crop productivity and production estimations in the context of food security, impact assessment, and model evaluation exercises. 相似文献
6.
利用基于作物潜在蒸散建立的相对湿润度指数和作物灾损率指标,分析1980—2009 年合肥地区6 个气象台站的常规观测资料和作物产量数据,研究合肥地区地表干湿状况变化和典型作物受旱的灾损情况,通过分析作物灾损率以及其与相对湿润度指数的关系,建立合肥地区两种典型作物（小麦和水稻）关于相对湿润度指数的旱灾风险等级标准。结果表明：30 年间合肥地区相对湿润度指数均属正常偏湿状态,南部地区较北部偏湿,同时地表湿润状况存在0.048/10 年的变干趋势。冬小麦关于相对湿润度指数累计值的不同干旱等级（轻、中、重旱）指数界限值为- 2.0983 和- 3.4281,水稻为- 0.9371和-2.5660。合肥地区水稻对土壤水分胁迫的耐受力较冬小麦弱,因受旱导致减产的风险较大。 相似文献
7.
田间试验的空间变异性及其统计控制 总被引：6，自引：1，他引：6
利用空间相关模型和传统方差分析模型对小麦和玉米3个田间试验产量数据进行了拟合与分析。结果表明，3个试验都显著存在空间变异，空间变异方差占据剩余变异方差的83.5%~0.4%；相对于传统随机完全区组分析法，空间相关模型法效应比较的标准误平均降低18.4%~14.2%，分析相对效率平均为1.50~1.36，因而比区组控制空间变异更有效；不同空间相关模型分析的结果呈现出一定的差异。建议利用空间相关模型分析田间试验，并利用Akaike信息准则（AIC）进行最佳空间相关模型选择。 相似文献
8.
旨在量化表征晋北半干旱地区的干旱强度及其时空特征以及对农作物产量的影响,基于朔州市6个气象站点1972—2017年的实测气象资料,分析该地区的降水、气温的变化趋势,利用标准化降水蒸散指数(SPEI)定量分析了朔州市不同时间尺度的干旱频率及强度的时空特征。结果表明：朔州市年均降水量变化趋势不显著,季节平均降水量规律中,春、秋、冬季的平均降水量呈现增加趋势,夏季平均降水量为减少趋势,其中仅有秋季平均降水量增加的趋势显著。平均气温方面,年均温呈现极为显著的上升趋势,春季平均气温增加的显著性最强。朔州市干旱频率在1992—2001年代表现最高,该年代也是极端干旱的高频率期。朔州市短时间尺度（3个月）的SPEI值(SPEI-3)在10年尺度上的干旱最长持续时间达8个月,发生在1992—2001年间。SPEI-12在10年尺度上呈现：在1982—1991年间的干旱最长持续时间达7个月。干旱特征影响了朔州市的农作物产量,朔州市干旱特征与农作物平均产量存在二次函数关系。研究结果可为该地区雨养农业的发展提供参考。 相似文献
9.
The spatial variability of soil properties is an important driver of yield variability at both field and regional scale. Thus, when using crop growth simulation models, the choice of spatial resolution of soil input data might be key in order to accurately reproduce observed yield variability. In this study we used four crop models (SIMPLACE<LINTUL-SLIM>, DSSAT-CSM, EPIC and DAISY) differing in the detail of modeling above-ground biomass and yield as well as of modeling soil water dynamics, water uptake and drought effects on plants to simulate winter wheat in two (agro-climatologically and geo-morphologically) contrasting regions of the federal state of North-Rhine-Westphalia (Germany) for the period from 1995 to 2008. Three spatial resolutions of soil input data were taken into consideration, corresponding to the following map scales: 1:50 000, 1:300 000 and 1:1 000 000. The four crop models were run for water-limited production conditions and model results were evaluated in the form of frequency distributions, depicted by bean-plots.In both regions, soil data aggregation had very small influence on the shape and range of frequency distributions of simulated yield and simulated total growing season evapotranspiration for all models. Further analysis revealed that the small influence of spatial resolution of soil input data might be related to: (a) the high precipitation amount in the region which partly masked differences in soil characteristics for water holding capacity, (b) the loss of variability in hydraulic soil properties due to the methods applied to calculate water retention properties of the used soil profiles, and (c) the method of soil data aggregation.No characteristic “fingerprint” between sites, years and resolutions could be found for any of the models. Our results support earlier recommendation to evaluate model results on the basis of frequency distributions since these offer quick and better insight into the distribution of simulation results as compared to summary statistics only. Finally, our results support conclusions from other studies about the usefulness of considering a multi-model approach to quantify the uncertainty in simulated yields introduced by the crop growth simulation approach when exploring the effects of scaling for regional yield impact assessments. 相似文献
10.
Jixiang Wu Krishna Bondalapati Karl Glover William Berzonsky Johnie N. Jenkins Jack C. McCarty 《Euphytica》2013,190(3):447-458
Genetic data collected from various plant breeding and genetic studies may not be replicated in field designs although field variation is always present. In this study, we addressed this problem using spring wheat (Triticum aestivum L.) trial data collected from two locations. There were no intralocation replications and an extended additive-dominance (AD) model was used to account for field variation. We numerically evaluated the data from simulations and estimated the variance components. For demonstration purposes we also analyzed three agronomic traits from the actual spring wheat data set. Results showed that these data could be effectively analyzed using an extended AD model, which was more comparable to a conventional AD model. Actual data analysis revealed that grain yield was significantly influenced by systematic field variation. Additive effects were significant for all traits and dominance effects were significant for plant height and time-to-flowering. Genetic effects were predicted and used to demonstrate that most spring wheat lines developed by the South Dakota State University breeding program (SD lines) exhibited good general combining ability effects for yield improvement. Thus, this study provides a general framework to appropriately analyze data in situations where field crop data are collected from non-replicated designs. 相似文献
11.
Wheat is one of the most important cultivated cereals worldwide. In Uruguay, the area increased from 153.000 ha to 453.000 ha between 2004 and 2012, nowadays representing 80% of the total winter crops area. As the high area of the crop, is common planting wheat in a field with wheat as previous winter crop (“wheat after wheat”). This practice leads to a high inoculum pressure of necrotrophic pathogens which guarantees disease inoculation mainly of Pyrenophora tritici-repentis (tan spot—TS) and Zymoseptoria tritici (septoria leaf blotch—SLB). There is strong evidence that integrated crop management practices such as nitrogen (N) fertilization, genetic resistance to leaf diseases and fungicides could mitigate yield losses associated with monoculture. However, the impacts of integrated technologies based on actual field data have not been reported before. We based our study in an on-farm wheat yield and management database to assess the previous winter crop effect on wheat yield under no-till systems. This database corresponds to a set of farmers grouped in CREA (Consorcio Regional de Experimentación Agrícola). A complete database of 1292 no-till wheat fields was analyzed. The effect of previous winter crop on yield and the impact of different technologies were estimated based on two approaches: (i) yield quartile analysis and (ii) yield frontier analysis. The crop rotation had a significant impact on yield. The practice of growing “wheat after wheat” was associated with a yield loss of ca 500 kg ha−1. The selection of a diseases resistant cultivar under “wheat after wheat” fields increases yields in ≈700 kg ha−1. The percentage of fields with an efficiency higher than 80% improved from 49 to 77% when a resistant cultivar to TS and SLB was selected, and when N fertilizer was applied earlier and in higher rates. Unexpectedly, only 18% of the “wheat after wheat” fields are applying these two technologies in scenarios under high inoculum pressure. This study, based in on-farm data, highlights the relevance of integrated disease management, and remarks the potential of this approach to minimize the interference of foliar diseases in fields with high inoculum pressure of stubble-borne pathogens. 相似文献
12.
Long-term field measured yield data provides good opportunity to assess the impacts of climate and management on crop production. This study used the yield results from a long-term field experiment (1979–2012) at Luancheng Experimental Station in the central part of the North China Plain (NCP) to analyze the seasonal yield variation of winter wheat (Triticum aestivum L.) under the condition of sufficient water supply. The yield change of winter wheat over the last 33 growing seasons was divided into three time periods: the 1980s, the 1990s, and the years of 2001–2012. The grain yield of winter wheat during the 1980s was relative stable. During the 1990s, the annual yield of this crop was continuously increased by 193 kg/ha/year (P < 0.01). While for the past 12 years, yield of winter wheat was maintained at relative higher level, but with larger seasonal yield variation than that back in 1980s. CERES-Wheat model was calibrated and was used to verify the effects of management practices on grain yield. Seven scenarios were simulated with and without improvements in management. The simulated results show that the yield of winter wheat was decreased by 5.3% during 1990s and by 9.2% during the recent 12 seasons, compared with that during 1980s, under the scenario that the yield of winter wheat was solely affected by weather. Seasonal yield variation caused by weather factors was around −39% to 20%, indicating the great effects of weather on yearly yield variation. Yield improvement by cultivars was around 24.7% during 1990s and 52.0% during the recent 12 seasons compared with that during 1980s. The yield improvement by the increase in soil fertility and chemical fertilizer input was 7.4% and 6.8% during the two periods, respectively. The initial higher soil fertility and chemical fertilizer input might be the reasons that the responses of crop production to the further increase in chemical fertilizer were small during the simulation period. Correlation analysis of the grain yield from the field measured data with weather factors showed that sunshine hours and diurnal temperature difference (DTR) were positively, and relative humidity was negatively related to grain yield of winter wheat. The climatic change trends in this area showed that the DTR and sunshine hours were declining. This type of climatic change trend might further negatively affect winter wheat production in the future. 相似文献
13.
Winter wheat production in northern China severely suffered from high temperatures and low relative humidity. However, the spatio-temporal pattern of heat stress and dry stress and the impacts of these multi-hazards on winter wheat yield have rarely been investigated. Using historical climate data, phenology data and yield records from 1980 to 2008, an analysis was performed to characterize the spatio-temporal variability of heat stress and dry stress in the post-heading stages of wheat growth in northern China. Additionally, these stresses’ impacts on winter wheat yield fluctuations were evaluated. Spatially, the central and northern parts of northern China have seen more serious heat stress, while greater dry stress has been observed in the northwest and north of the research area. Temporally, the heat stress has increased in the western part but decreased in the central and eastern parts of research area. Dry stress has aggravated in the entire northern China during the past decades, indicating the complexity of the exposure to adverse climate conditions. These two hazards (heat stress and dry stress) have contributed significant yield loss (up to 1.28% yield yr−1) in most parts of the research region. The yield in the west was more sensitive to heat stress, and dry stress was the main hazard in the south. Additionally, the opposite spatial pattern between the sensitivity and exposure revealed that the climate is not the only factor controlling the yield fluctuation, the local adaptation measures used to mitigate negative influences of extreme events should not be ignored. In general, this study highlighted a focus on the impacts of multi-hazards on agricultural production, and an equal importance of considering local adaptation ability during the evaluation of agricultural risk in the future. Additionally, paying more attention to higher sensitive areas and to more reasonable and practical adaptive strategies is critical and significant for food supply security. 相似文献
14.
空间统计分析在作物育种品系选择中的效果 总被引：2，自引：0，他引：2
为了研究空间统计分析法在作物育种田间试验品系选择中的效果,采用剩余误差空间相关线性混合模型对一个具有56个品系的小麦育种随机区组设计田间试验产量资料进行了空间统计分析。运用地理统计学中的半变异函数法确定剩余误差空间协方差的函数。结果表明,试验的剩余误差存在着典型的空间相关性,利用剩余误差空间协方差结构的信息可降低品系效应估计的误差和提高品系效应差异F检验与t检验的效率。此外,空间分析法对品系效应估计受试验条件不均匀的影响小,可导致较经典方差分析法不同的品系排序和优系选择结果。 相似文献
15.
Precision agriculture techniques imply a spatial management of fields and to do so a good understanding of the spatial and temporal variability of yield is needed. Average yield data from seven irrigated maize fields were used to study the yield pattern considering the distance of plants to flow accumulation lines. It was found that there is a significant correlation between average yield and distance to flow accumulation lines (DFL). This correlation is best represented by a polynomial function. The most common shape of the yield pattern curve considering the distance to flow accumulation lines shows that there is an increase in average yield with DFL from 0 to 12.5–17.5 m. Near the flow lines the average yield presents lower values due to drainage problems causing plant growth problems. It was also observed higher yield variability near the flow lines. For higher distances from the flow lines there is a continuous decrease in average yield due to less water availability and other variations of soil properties. 相似文献
16.
Data from aerial infrared photographs have recently been proposed as a complementary analytical tool for evaluating genotype performance in breeders' trials. Our objective was to establish the relationships between spring wheat grain yield and remotely-sensed data in a variety experiment. Large genotype differences (P ≤ 0.05) in grain yield, red, and near infrared reflectance values occurred. Significant (P ≤ 0.05) regressions between grain yield and remoteley-sensed data were observed for two dates of flight, but these functions varied between dates of flight. A normalized difference vegetative index, as an estimate of crop productivity, indicated that spring wheats with the highest grain yields may show correspondingly high dry matter production. However, low r2 values for the remotely-sensed values suggest that much of the variability is not explained by these models. Future research must develop more accurate methods of remotely-sensed analysis, including standardizing the images, identifying the correct time with respect to stage of crop development for infrared photographs, incorporating crop harvest index data into the models, and adjusting for identified spatial variation. 相似文献
17.
华北地区冬小麦产量潜力分布特征及其影响因素 总被引：5，自引：0，他引：5
利用华北地区农业气象观测站作物资料,验证APSIM-Wheat作物模拟模型区域尺度有效性,结合1961-2007年47年逐日气候资料,分析冬小麦潜在产量、水分限制产量和水氮限制产量时空分布特征,明确了气候因素对冬小麦不同等级产量潜力分布特征的影响程度。对APSIM-Wheat模型在华北地区区域尺度上进行验证,结果显示区域化模型在华北地区有较好的适用性。华北地区冬小麦各层次产量在时间上总体呈下降趋势,空间上呈带状分布,不同层次产量空间分布特征有所差别：冬小麦潜在产量从东北向西南减少,水分限制产量从东南向西北递减,水氮限制产量从东向西先增加后降低在山东济宁地区达到最大;河北省为冬小麦潜在产量和水氮限制产量的高值区,同时为水分限制产量的低值区,增加灌溉是提高其产量的主要途径;山东省为冬小麦潜在产量和水分限制产量的高值区,水氮限制产量的低值区,增施氮肥是提高其产量的主要途径;河南省为冬小麦潜在产量的低值区,辐射是其主要限制因素。决定冬小麦潜在产量时空分布特征的最主要气候要素为生长季内总辐射,总辐射与潜在产量呈极显著正相关关系;决定冬小麦水分限制产量分布特征的最主要气候要素为冬小麦生长季内降水量,呈极显著正相关关系;气候要素对于冬小麦水氮限制产量空间分布特征的解释方差较小,仅为0.48,故土壤等其他因素对其空间分布影响较大。气候变化背景下,如不改变作物品种,冬小麦各级产量潜力呈下降趋势,造成其下降的主要原因为总辐射下降以及随积温增加冬小麦生长季缩短,决定冬小麦产量潜力空间分布的主要因素为总辐射和降水量。 相似文献
18.
四川省粮食单产时空变化及其动因分析 总被引：2，自引：2，他引：0
为了揭示四川省粮食单产时空变化特征和影响粮食单产变化的主要原因。基于1988-2008年四川省21个市州区统计数据,运用统计分析和灰色关联分析方法,分析该省粮食单产时空变化特征及其动因。研究结果表明：（1）四川省多年平均粮食单产高于全国平均水平,各市州区粮食单产总体呈增长趋势。（2）各市州区粮食单产水平差异显著,最高的是德阳市,最低的是甘孜州,前者为后者的2.5倍,市州区间单产水平差距逐渐减小。（3）粮食单产水平显著上升的市州区个数占总数的一半以上,除资阳市粮食单产略有减少外,其他市州区稳中略有增加。（4）化肥用量、农业生产资料价格指数和粮食收购价格指数是影响粮食单产时空变化的主要动因。笔者提出增加农业生产物质投入,完善农业基础设施和改良中低产田是挖掘粮食单产,提高粮食产量和增强粮食安全保障的重要途径。 相似文献
19.
《European Journal of Agronomy》2006,24(3):226-235
The North China Plain (NCP) is one of the major winter wheat (Triticum aestivum L.) producing areas in China. Current wheat yields in the NCP stabilize around 5 Mg ha−1 while the demand for wheat in China is growing due to the increase in population and the change in diet. Since options for area expansion of winter wheat are limited, the production per unit of area need to be increased. The objective of this study is to quantify the production potential of winter wheat in the NCP taking into account the spatial and temporal variability caused by climate. We use a calibrated crop growth simulation model to quantify wheat yields for potential and water-limited production situations using 40 years of weather data from 32 meteorological stations in the NCP. Simulation results are linked to a Geographic Information System (GIS) facilitating their presentation and contributing to the identification of hotspots for interventions aimed at yield improvements. In the northern part of the NCP, average simulated potential yields of winter wheat go up to 9.7 Mg ha−1, while average water-limited yields only reach 3 Mg ha−1. In the southern part of the NCP, both average potential and water-limited yields are about 7.5 Mg ha−1. Rainfall is the limiting factor to winter wheat yields in the northern part of the NCP, while in the southern part, the joint effect of low radiation and high temperature are major limiting factors. Temporal variation in potential yields throughout the NCP is low in contrast with the temporal variation in water-limited yields, which is especially great in the northern part. The study calls for the collection of location-specific and disaggregated irrigated and rainfed wheat yield statistics in the NCP facilitating the identification of hotspots for improvement of current wheat yields. 相似文献
20.
气候变异对内蒙古武川县麦类作物产量的影响 总被引：3，自引：0，他引：3
【研究目的】内蒙古武川县位于阴山北麓农牧交错带温凉旱区,是春小麦、莜麦等喜凉作物的适宜产地,但由于气候的年际波动,产量低而不稳。通过分析产量与气候的关系,可采取措施减轻潜在的气候风险。【方法】笔者根据产量统计资料、生育期观测资料和历年气象数据,用相关分析法分析各时期平均温度、日照时数、降水量三个气候因子对春小麦、莜麦产量的影响,建立多因子产量评估模式。【结果】结果表明,武川小麦和莜麦的丰歉与生长季各月的平均气温及其总和呈负相关,与生长季各月降水量及生长季降水之和呈正相关,与日照时数关系不显著。通过找出影响产量丰歉的气象指标因子进行多元回归分析,得出产量的评价模型,可用于武川县麦类作物产量丰歉年评估。【结论】研究认为,气候暖干化将增加武川麦类作物生产的气候风险 相似文献