Crop planting dates: an analysis of global patterns

Aim To assemble a data set of global crop planting and harvesting dates for 19 major crops, explore spatial relationships between planting date and climate for two of them, and compare our analysis with a review of the literature on factors that drive decisions on planting dates. Location Global. Methods We digitized and georeferenced existing data on crop planting and harvesting dates from six sources. We then examined relationships between planting dates and temperature, precipitation and potential evapotranspiration using 30‐year average climatologies from the Climatic Research Unit, University of East Anglia (CRU CL 2.0). Results We present global planting date patterns for maize, spring wheat and winter wheat (our full, publicly available data set contains planting and harvesting dates for 19 major crops). Maize planting in the northern mid‐latitudes generally occurs in April and May. Daily average air temperatures are usually c. 12–17 °C at the time of maize planting in these regions, although soil moisture often determines planting date more directly than does temperature. Maize planting dates vary more widely in tropical regions. Spring wheat is usually planted at cooler temperatures than maize, between c. 8 and 14 °C in temperate regions. Winter wheat is generally planted in September and October in the northern mid‐latitudes. Main conclusions In temperate regions, spatial patterns of maize and spring wheat planting dates can be predicted reasonably well by assuming a fixed temperature at planting. However, planting dates in lower latitudes and planting dates of winter wheat are more difficult to predict from climate alone. In part this is because planting dates may be chosen to ensure a favourable climate during a critical growth stage, such as flowering, rather than to ensure an optimal climate early in the crop's growth. The lack of predictability is also due to the pervasive influence of technological and socio‐economic factors on planting dates.     

Modelling the role of agriculture for the 20th century global terrestrial carbon balance

In order to better assess the role of agriculture within the global climate‐vegetation system, we present a model of the managed planetary land surface, Lund–Potsdam–Jena managed Land (LPJmL), which simulates biophysical and biogeochemical processes as well as productivity and yield of the most important crops worldwide, using a concept of crop functional types (CFTs). Based on the LPJ‐Dynamic Global Vegetation Model, LPJmL simulates the transient changes in carbon and water cycles due to land use, the specific phenology and seasonal CO₂ fluxes of agricultural‐dominated areas, and the production of crops and grazing land. It uses 13 CFTs (11 arable crops and two managed grass types), with specific parameterizations of phenology connected to leaf area development. Carbon is allocated daily towards four carbon pools, one being the yield‐bearing storage organs. Management (irrigation, treatment of residues, intercropping) can be considered in order to capture their effect on productivity, on soil organic carbon and on carbon extracted from the ecosystem. For transient simulations for the 20th century, a global historical land use data set was developed, providing the annual cover fraction of the 13 CFTs, rain‐fed and/or irrigated, within 0.5° grid cells for the period 1901–2000, using published data on land use, crop distributions and irrigated areas. Several key results are compared with observations. The simulated spatial distribution of sowing dates for temperate cereals is comparable with the reported crop calendars. The simulated seasonal canopy development agrees better with satellite observations when actual cropland distribution is taken into account. Simulated yields for temperate cereals and maize compare well with FAO statistics. Monthly carbon fluxes measured at three agricultural sites also compare well with simulations. Global simulations indicate a ∼24% (respectively ∼10%) reduction in global vegetation (respectively soil) carbon due to agriculture, and 6–9 Pg C of yearly harvested biomass in the 1990s. In contrast to simulations of the potential natural vegetation showing the land biosphere to be an increasing carbon sink during the 20th century, LPJmL simulates a net carbon source until the 1970s (due to land use), and a small sink (mostly due to changing climate and CO₂) after 1970. This is comparable with earlier LPJ simulations using a more simple land use scheme, and within the uncertainty range of estimates in the 1980s and 1990s. The fluxes attributed to land use change compare well with Houghton's estimates on the land use related fluxes until the 1970s, but then they begin to diverge, probably due to the different rates of deforestation considered. The simulated impacts of agriculture on the global water cycle for the 1990s are∼5% (respectively∼20%) reduction in transpiration (respectively interception), and∼44% increase in evaporation. Global runoff, which includes a simple irrigation scheme, is practically not affected.     

Agroclimatic conditions in Europe under climate change

To date, projections of European crop yields under climate change have been based almost entirely on the outputs of crop‐growth models. While this strategy can provide good estimates of the effects of climatic factors, soil conditions and management on crop yield, these models usually do not capture all of the important aspects related to crop management, or the relevant environmental factors. Moreover, crop‐simulation studies often have severe limitations with respect to the number of crops covered or the spatial extent. The present study, based on agroclimatic indices, provides a general picture of agroclimatic conditions in western and central Europe (study area lays between 8.5°W–27°E and 37–63.5°N), which allows for a more general assessment of climate‐change impacts. The results obtained from the analysis of data from 86 different sites were clustered according to an environmental stratification of Europe. The analysis was carried for the baseline (1971–2000) and future climate conditions (time horizons of 2030, 2050 and with a global temperature increase of 5 °C) based on outputs of three global circulation models. For many environmental zones, there were clear signs of deteriorating agroclimatic condition in terms of increased drought stress and shortening of the active growing season, which in some regions become increasingly squeezed between a cold winter and a hot summer. For most zones the projections show a marked need for adaptive measures to either increase soil water availability or drought resistance of crops. This study concludes that rainfed agriculture is likely to face more climate‐related risks, although the analyzed agroclimatic indicators will probably remain at a level that should permit rainfed production. However, results suggests that there is a risk of increasing number of extremely unfavorable years in many climate zones, which might result in higher interannual yield variability and constitute a challenge for proper crop management.     

Mind the gap: how do climate and agricultural management explain the ‘yield gap’ of croplands around the world?

Aim As the demands for food, feed and fuel increase in coming decades, society will be pressed to increase agricultural production – whether by increasing yields on already cultivated lands or by cultivating currently natural areas – or to change current crop consumption patterns. In this analysis, we consider where yields might be increased on existing croplands, and how crop yields are constrained by biophysical (e.g. climate) versus management factors. Location This study was conducted at the global scale. Methods Using spatial datasets, we compare yield patterns for the 18 most dominant crops within regions of similar climate. We use this comparison to evaluate the potential yield obtainable for each crop in different climates around the world. We then compare the actual yields currently being achieved for each crop with their ‘climatic potential yield’ to estimate the ‘yield gap’. Results We present spatial datasets of both the climatic potential yields and yield gap patterns for 18 crops around the year 2000. These datasets depict the regions of the world that meet their climatic potential, and highlight places where yields might potentially be raised. Most often, low yield gaps are concentrated in developed countries or in regions with relatively high‐input agriculture. Main conclusions While biophysical factors like climate are key drivers of global crop yield patterns, controlling for them demonstrates that there are still considerable ranges in yields attributable to other factors, like land management practices. With conventional practices, bringing crop yields up to their climatic potential would probably require more chemical, nutrient and water inputs. These intensive land management practices can adversely affect ecosystem goods and services, and in turn human welfare. Until society develops more sustainable high‐yielding cropping practices, the trade‐offs between increased crop productivity and social and ecological factors need to be made explicit when future food scenarios are formulated.     

Response of Spring Wheat (Triticum aestivum L.) Quality Traits and Yield to Sowing Date

The unpredictability and large fluctuation of the climatic conditions in rainfed regions do affect spring wheat yield and grain quality. These variations offer the opportunity for the production of better quality wheat. The effect of variable years, locations and sowing managements on wheat grain yield and quality was studied through field experiments using three genotypes, three locations for two years under rainfed conditions. The two studied years as contrasting years at three locations and sowing dates depicted variability in temperature and water stress during grain filling which resulted considerable change in grain yield and quality. Delayed sowing, years (2009–10) and location (Talagang) with high temperature and water stress resulted increased proline, and grain quality traits i.e. grain protein (GP) and grain ash (GA) than optimum conditions (during 2008–09, at Islamabad and early sowing). However, opposite trend was observed for dry gluten (DG), sodium dodecyl sulphate (SDS), SPAD content and grain yield irrespective of genotypes. The influence of variable climatic conditions was dominant in determining the quality traits and inverse relationship was observed among some quality traits and grain yield. It may be concluded that by selecting suitable locations and different sowing managements for subjecting the crop to desirable environmental conditions (temperature and water) quality traits of wheat crop could be modified.     

Effects of precipitation and temperature on crop production variability in northeast Iran

Climate variability adversely impacts crop production and imposes a major constraint on farming planning, mostly under rainfed conditions, across the world. Considering the recent advances in climate science, many studies are trying to provide a reliable basis for climate, and subsequently agricultural production, forecasts. The El Niño-Southern Oscillation phenomenon (ENSO) is one of the principle sources of interannual climatic variability. In Iran, primarily in the northeast, rainfed cereal yield shows a high annual variability. This study investigated the role played by precipitation, temperature and three climate indices [Arctic Oscillation (AO), North Atlantic Oscillation (NAO) and NINO 3.4] in historically observed rainfed crop yields (1983–2005) of both barley and wheat in the northeast of Iran. The results revealed differences in the association between crop yield and climatic factors at different locations. The south of the study area is a very hot location, and the maximum temperature proved to be the limiting and determining factor for crop yields; temperature variability resulted in crop yield variability. For the north of the study area, NINO 3.4 exhibited a clear association trend with crop yields. In central locations, NAO provided a solid basis for the relationship between crop yields and climate factors.     

基于ORYZA2000模型的北京地区旱稻适宜播种期分析

确定适宜播种期是制定合理的作物栽培管理方案的关键内容之一。在作物模型ORYZA2000有效性验证的基础上,以北京地区为例,利用该模型结合长期历史气候资料,对确定旱稻适宜播种期做了初步研究。结果表明：在不考虑水分因子条件下,北京地区旱稻297安全播期的范围较广,多年平均为3月26日-6月4日;受温度升高的影响,最早播期有提前趋势,而最晚播种期有延后趋势。在同一年份内,播期不同旱稻的产量也有一定的变化,呈现为先升高而后降低的趋势。播期过早或过晚导致生育期平均温度偏低是影响穗干物质累积且造成减产的主要原因,在适宜的播期范围内才能获得高产。以90%-100%当年最高产量潜力作为适宜播期的产量指标,确定北京地区旱稻297的适宜播期变化在5月11日-5月19日之间,相应的产量变化在6689-7257 kg/hm2范围内。研究方法可为其他地区旱稻的播期研究提供借鉴。     

Field observations on nitrogen catch crops. I. Potential and actual growth and nitrogen accumulation in relation to sowing date and crop species

In temperate climates with a precipitation surplus during autumn and winter, nitrogen catch crops can help to reduce nitrogen losses from cropping systems by absorbing nitrogen from the soil and transfer it to a following main crop. The actual and potential accumulation of dry matter and nitrogen in catch crops were studied in the field during four seasons with winter rye (Secale cereale) and forage rape (Brassica napus ssp. oleifera (Metzg.) Sinsk) or oil radish (Raphanus sativus spp. oleiferus (DC.) Metzg.). Sowing dates were end of August and three and six weeks later. Potential nitrogen accumulation, Y (g m^-2), could be summarized with Y = 96 –0.34 X, where X is the day number in the year of the sowing date (range: late August till end of September). Species were compared in their performance, looking at differences in specific leaf area, leaf weight ratio, leaf area ratio, light extinction and persistence during frost. The rate of dry matter accumulation in intervals of 14 days appeared to be determined primarily by the amount of radiation intercepted. A regression, forced through the origin, gave as a common slope 1.12 g dry matter accumulated per MJ intercepted global radiation, irrespective of season, species, sowing date or nitrogen treatment (period from ca. day 250 to day 310). From this result the inference is made that leaf expansion is a key process, determining the performance of catch crop species under varying environmental conditions.     

High night temperatures during grain number determination reduce wheat and barley grain yield: a field study

Warm nights are a widespread predicted feature of climate change. This study investigated the impact of high night temperatures during the critical period for grain yield determination in wheat and barley crops under field conditions, assessing the effects on development, growth and partitioning crop‐level processes driving grain number per unit area (GN). Experiments combined: (i) two contrasting radiation and temperature environments: late sowing in 2011 and early sowing in 2013, (ii) two well‐adapted crops with similar phenology: bread wheat and two‐row malting barley and (iii) two temperature regimes: ambient and high night temperatures. The night temperature increase (ca. 3.9 °C in both crops and growing seasons) was achieved using purpose‐built heating chambers placed on the crop at 19:000 hours and removed at 7:00 hours every day from the third detectable stem node to 10 days post‐flowering. Across growing seasons and crops, the average minimum temperature during the critical period ranged from 11.2 to 17.2 °C. Wheat and barley grain yield were similarly reduced under warm nights (ca. 7% °C^?1), due to GN reductions (ca. 6% °C^?1) linked to a lower number of spikes per m². An accelerated development under high night temperatures led to a shorter critical period duration, reducing solar radiation capture with negative consequences for biomass production, GN and therefore, grain yield. The information generated could be used as a starting point to design management and/or breeding strategies to improve crop adaptation facing climate change.     

区域种植业气候适宜度及其对种植活动的响应——以四川省盐亭县为例

在分析盐亭县近63年来(1950—2012)种植业生产发展的基础上,选取该县农村社会经济条件相对稳定的近32年(1981—2012)为研究时段。运用农业生态气候适宜度方法,依据水稻、红薯、玉米、小麦和油菜等5种主要作物生育期的光、热、水等气候条件,分别估算各种作物的资源适宜指数、效能适宜指数和利用指数,构建小尺度区域种植业气候适宜度模型和种植活动对区域种植业气候适宜度的影响度模型,进行小尺度区域种植业气候适宜度以及种植活动对种植业气候适宜度的影响度估算,并对种植业生产对气候变化的适应进行探讨。研究结果表明,(1)近32年来盐亭县大春作物的平均资源适宜指数、效能适宜指数和利用指数(分别为0.578、0.281和48.37%)均大于小春作物(分别为0.304、0.128和42.24%),大春作物的气候适宜度高于小春作物,且作物间的气候适宜度差异较大。(2)受季风气候波动的影响,该县作物气候适宜度有明显的年际波动;该县近32年来气候变化对大春作物气候适宜度有轻微不利影响,而对小春作物气候适宜度趋于有利。(3)盐亭县近32年来种植业平均的资源适宜指数为0.466、效能适宜指数为0.212、利用指数为45.49%;受5种作物资源适宜指数、效能适宜指数,以及作物播种面积与产量年际波动的综合影响,该县种植业气候适宜度亦有明显的年际波动;气候变化对该县种植业气候适宜度总体上有不利影响。(4)近32年来该县种植活动对种植业气候适宜度的影响度平均值为0.00092,其年际波动较大。通过作物种植组合结构的调整,在20世纪90年代中期前对种植业气候适宜度的提高有微弱的正向影响,对气候变化有一定程度的适应;而后期则有负向作用。     

Potential impact of climate change on selected agricultural crops in north-eastern Austria

The vulnerability and adaptation of major agricultural crops to various soils in north‐eastern Austria under a changing climate were investigated. The CERES crop model for winter wheat and the CROPGRO model for soybean were validated for the agrometeorological conditions in the selected region. The simulated winter wheat and soybean yields in most cases agreed with the measured data. Several incremental and transient global circulation model (GCM) climate change scenarios were created and used in the study. In these scenarios, annual temperatures in the selected region are expected to rise between 0.9 and 4.8 °C from the 2020s to the 2080s. The results show that warming will decrease the crop‐growing duration of the selected crops. For winter wheat, a gradual increase in air temperature resulted in a yield decrease. Incremental warming, especially in combination with an increase in precipitation, leads to higher soybean yield. A drier climate will reduce soybean yield, especially on soils with low water storage capacity. All transient GCM climate change scenarios for the 21st century, including the adjustment for only air temperature, precipitation and solar radiation, projected reductions of winter wheat yield. However, when the direct effect of increased levels of CO₂ concentration was assumed, all GCM climate change scenarios projected an increase in winter wheat yield in the region. The increase in simulated soybean yield for the 21st century was primarily because of the positive impact of warming and especially of the beneficial influence of the direct CO₂ effect. Changes in climate variability were found to affect winter wheat and soybean yield in various ways. Results from the adaptation assessments suggest that changes in sowing date, winter wheat and soybean cultivar selection could significantly affect crop production in the 21st century.     

The implication of irrigation in climate change impact assessment: a European‐wide study

This study evaluates the impacts of projected climate change on irrigation requirements and yields of six crops (winter wheat, winter barley, rapeseed, grain maize, potato, and sugar beet) in Europe. Furthermore, the uncertainty deriving from consideration of irrigation, CO₂ effects on crop growth and transpiration, and different climate change scenarios in climate change impact assessments is quantified. Net irrigation requirement (NIR) and yields of the six crops were simulated for a baseline (1982–2006) and three SRES scenarios (B1, B2 and A1B, 2040–2064) under rainfed and irrigated conditions, using a process‐based crop model, SIMPLACE . We found that projected climate change decreased NIR of the three winter crops in northern Europe (up to 81 mm), but increased NIR of all the six crops in the Mediterranean regions (up to 182 mm yr^?1). Climate change increased yields of the three winter crops and sugar beet in middle and northern regions (up to 36%), but decreased their yields in Mediterranean countries (up to 81%). Consideration of CO₂ effects can alter the direction of change in NIR for irrigated crops in the south and of yields for C3 crops in central and northern Europe. Constraining the model to rainfed conditions for spring crops led to a negative bias in simulating climate change impacts on yields (up to 44%), which was proportional to the irrigation ratio of the simulation unit. Impacts on NIR and yields were generally consistent across the three SRES scenarios for the majority of regions in Europe. We conclude that due to the magnitude of irrigation and CO₂ effects, they should both be considered in the simulation of climate change impacts on crop production and water availability, particularly for crops and regions with a high proportion of irrigated crop area.     

中国北方气候暖干化对粮食作物的影响及应对措施

东北、华北和西北50a来的平均气温增幅高于全国平均水平,气候变暖明显,尤其冬季增温最显著。区域增暖的极端最低气温远比极端最高气温的贡献大。东北、华北大部、西北东部降水量明显减少,平均每10a减少20—40mm,尤其春夏季减少最明显。这种趋势一直延续到20世纪90年代以后,干旱化趋势非常突出。在综述我国北方现代气候变化基本特征是暖干化的基础上,重点阐述了喜凉作物冬小麦、春小麦、马铃薯和喜温作物水稻、玉米、谷子、糜子等7种主要粮食作物的生长发育、品种熟性、种植区域与面积、产量与品质等对气候暖干化的响应特征。揭示了气候暖干化使春播作物播期提早,苗期生长发育速度加快,营养生长期提前,生殖生长期和全生育期延长;秋作物发育期推迟,生殖生长期和全生长期延长;越冬作物播期推迟,越冬死亡率降低,种植风险减少,春初提前返青,生殖生长期提早,全生育期缩短。使作物适宜种植区域向高纬度高海拔扩展;品种熟性向偏中晚熟高产品种发展;喜温作物和越冬作物以及冷凉气候区的作物种植面积迅速扩大;在旱作区种植不较耐旱的玉米、春小麦等作物种植面积受到制约。对雨养农业区的作物气候产量影响严重,尤其对不够耐旱的小麦和玉米的气候产量受影响最大;对较耐旱的谷子、糜子、马铃薯等影响较轻。从作物属性而言,对喜温作物水稻、玉米和越冬作物冬小麦有利于气候产量提高;对喜凉作物春小麦和马铃薯的气候产量将产生不利影响。同时,提出了从5个方面应对气候暖干化的技术措施,调整作物种植结构,确保粮食生产安全;根据不同气候年型调整各种作物种植比例;针对不同气候区域发展优势作物和配置作物种植格局;采取不同栽培技术和管理模式应对气候变化;采取综合配套技术提髙抵御灾害能力。为粮食作物安全生产和种植结构调整与布局提供科学依据。     

Development and assessment of a coupled crop–climate model

It is well established that crop production is inherently vulnerable to variations in the weather and climate. More recently the influence of vegetation on the state of the atmosphere has been recognized. The seasonal growth of crops can influence the atmosphere and have local impacts on the weather, which in turn affects the rate of seasonal crop growth and development. Considering the coupled nature of the crop–climate system, and the fact that a significant proportion of land is devoted to the cultivation of crops, important interactions may be missed when studying crops and the climate system in isolation, particularly in the context of land use and climate change.
To represent the two-way interactions between seasonal crop growth and atmospheric variability, we integrate a crop model developed specifically to operate at large spatial scales (General Large Area Model for annual crops) into the land surface component of a global climate model (GCM; HadAM3). In the new coupled crop–climate model, the simulated environment (atmosphere and soil states) influences growth and development of the crop, while simultaneously the temporal variations in crop leaf area and height across its growing season alter the characteristics of the land surface that are important determinants of surface fluxes of heat and moisture, as well as other aspects of the land-surface hydrological cycle. The coupled model realistically simulates the seasonal growth of a summer annual crop in response to the GCM's simulated weather and climate. The model also reproduces the observed relationship between seasonal rainfall and crop yield. The integration of a large-scale single crop model into a GCM, as described here, represents a first step towards the development of fully coupled crop and climate models. Future development priorities and challenges related to coupling crop and climate models are discussed.     

Negative effects of climate warming on maize yield are reversed by the changing of sowing date and cultivar selection in Northeast China

Northeast China (NEC) accounts for about 30% of the nation's maize production in China. In the past three decades, maize yields in NEC have increased under changes in climate, cultivar selection and crop management. It is important to investigate the contribution of these changing factors to the historical yield increases to improve our understanding of how we can ensure increased yields in the future. In this study, we use phenology observations at six sites from 1981 to 2007 to detect trends in sowing dates and length of maize growing period, and then combine these observations with in situ temperature data to determine the trends of thermal time in the maize growing period, as a measure of changes in maize cultivars. The area in the vicinity of these six sites accounts for 30% of NEC's total maize production. The agricultural production systems simulator, APSIM‐Maize model, was used to separate the impacts of changes in climate, sowing dates and thermal time requirements on maize phenology and yields. In NEC, sowing dates trended earlier in four of six sites and maturity dates trended later by 4–21 days. Therefore, the period from sowing to maturity ranged from 2 to 38 days longer in 2007 than it was in 1981. Our results indicate that climate trends alone would have led to a negative impact on maize. However, results from the adaptation assessments indicate that earlier sowing dates increased yields by up to 4%, and adoption of longer season cultivars caused a substantial increase in yield ranging from 13% to 38% over the past 27 years. Therefore, earlier sowing dates and introduction of cultivars with higher thermal time requirements in NEC have overcome the negative effects of climate change and turned what would have otherwise been a loss into a significant increase in maize yield.     

Diversifying crops for food and nutrition security – a case of teff

There are more than 50000 known edible plants in the world, yet two‐thirds of global plant‐derived food is provided by only three major cereals – maize (Zea mays), wheat (Triticum aestivum) and rice (Oryza sativa). The dominance of this triad, now considered truly global food commodities, has led to a decline in the number of crop species contributing to global food supplies. Our dependence on only a few crop species limits our capability to deal with challenges posed by the adverse effects of climate change and the consequences of dietary imbalance. Emerging evidence suggests that climate change will cause shifts in crop production and yield loss due to more unpredictable and hostile weather patterns. One solution to this problem is through the wider use of underutilised (also called orphan or minor) crops to diversify agricultural systems and food sources. In addition to being highly nutritious, underutilised crops are resilient in natural and agricultural conditions, making them a suitable surrogate to the major crops. One such crop is teff [Eragrostis tef (Zucc.) Trotter], a warm‐season annual cereal with the tiniest grain in the world. Native to Ethiopia and often the sustenance for local small farmers, teff thrives in both moisture‐stressed and waterlogged soil conditions, making it a dependable staple within and beyond its current centre of origin. Today, teff is deemed a healthy wheat alternative in the West and is sought‐after by health aficionados and those with coeliac disease or gluten sensitivity. The blooming market for healthy food is breathing new life into this underutilised crop, which has received relatively limited attention from mainstream research perhaps due to its ‘orphan crop’ status. This review presents the past, present and future of an ancient grain with a potential beyond its size.     

Cover crops mitigate direct greenhouse gases balance but reduce drainage under climate change scenarios in temperate climate with dry summers

Cover crops provide ecosystem services such as storing atmospheric carbon in soils after incorporation of their residues. Cover crops also influence soil water balance, which can be an issue in temperate climates with dry summers as for example in southern France and Europe. As a consequence, it is necessary to understand cover crops' long‐term influence on greenhouse gases (GHG) and water balances to assess their potential to mitigate climate change in arable cropping systems. We used the previously calibrated and validated soil–crop model STICS to simulate scenarios of cover crop introduction to assess their influence on rainfed and irrigated cropping systems and crop rotations distributed among five contrasted sites in southern France from 2007 to 2052. Our results showed that cover crops can improve mean direct GHG balance by 315 kg CO₂e ha⁻¹ year⁻¹ in the long term compared to that of bare soil. This was due mainly to an increase in carbon storage in the soil despite a slight increase in N₂O emissions which can be compensated by adapting fertilization. Cover crops also influence the water balance by reducing mean annual drainage by 20 mm/year but increasing mean annual evapotranspiration by 20 mm/year compared to those of bare soil. Using cover crops to improve the GHG balance may help to mitigate climate change by decreasing CO₂e emitted in cropping systems which can represent a decrease from 4.5% to 9% of annual GHG emissions of the French agriculture and forestry sector. However, if not well managed, they also could create water management issues in watersheds with shallow groundwater. Relationships between cover crop biomass and its influence on several variables such as drainage, carbon sequestration, and GHG emissions could be used to extend our results to other conditions to assess the cover crops' influence in a wider range of areas.     

基于GIS的黄土丘陵沟壑区作物生产潜力模拟研究

从YIELD模型的来源、输入文件及基本参数,模型中作物生产力计算各个子模型以及计算流程4个方面作了简单的叙述,以黄土丘陵沟壑区典型小流域晋西狼窝沟为例,在地理信息系统（GIS）技术十,应用YILD模型对该流域的作物生产潜力进行了模拟,并从作物类型,地类,耕作措施及气候条件4个方面对影响该流域作物产量的因素进行了分析。结果表明,该模型对不同作物的模拟产量在总体上与实体产量基本相符合,表明模型可以应用于黄土丘陵沟壑区的作物产量模拟之中,对于不同地类来说,坝地的土壤水分和以力条件明显高于梯田和坡耕地,因而坝地的模拟产量地高于梯田和坡地,但三者之间的差距没有实测产量显著,耕作措施是提高作物生产力的有效途径,对地膜覆盖,梯田以及施肥等耕作措施的模拟产量表明,这3种耕作措施均能有效的物生产力;其产量提高率均平均在85％以上,其中以施肥对作物的增产作用最大,增产率高达95％,,这与实测产量资料基本一致;气候条件是影响作物生产的直接因素,模拟结果表明模型对降水量和温度等气候条件十分敏感,不同年份降水量和温度的差异将直接导致作物生产力的显著不同。对YIELD模型的模拟结果分析表明,该模型可以有效地应用于黄土丘陵沟壑区的作物生产潜力研究。     

气候变化对甘肃省粮食生产的影响研究进展

甘肃省气候自1986年起向整体暖干化、局部暖湿化转型突变.与1960年相比,转型后2010年平均气温升高了1.1 ℃,平均降水量减少了28 mm,干旱半干旱区南移约50 km.气候变暖使甘肃省主要作物生育期有效积温增加,生长期延长,熟性、布局和种植制度改变,宜种区和种植海拔增加,多熟制北移,夏粮面积缩小,秋粮面积增大.弱冬性、中晚熟品种逐步取代强冬性、中早熟品种,有利于提高光温利用率,增加产量.暖湿型气候增加了绿洲灌区作物的气候生产力,暖干型气候降低了雨养农业区的气候产量,水分和肥力条件是决定因素.以提高有限降水利用率和利用效率、改善和提升土壤质量及肥力为核心,选育强抗逆、弱冬性、中晚熟、高水分利用效率的作物新品种,建立适温、适水的种植结构和种植制度,是甘肃省应对气候变化进行粮食生产的主要发展方向.     

Disease assessment methods and their use in simulating growth and yield of peanut crops affected by leafspot disease

Peanut (Arachis hypogaea) crops in Benin often experience late leafspot (Cercosporidium personatum), which causes severe yield losses associated with leaf defoliation and necrosis. The objective of this research was to determine the best method of disease assessment and to test its utility in the CROPGRO‐peanut model to simulate growth and yield as affected by late leafspot in early and late maturing peanut cultivars grown at different sowing dates under rain‐fed conditions (without irrigation) in northern Benin. Two peanut cultivars TS 32‐1 and 69–101 were sown on three dates between May and August during 1998 and 1999. In both years there was severe occurrence of late leafspot and the progression of disease was earlier and faster with later sowing dates. Overall, the long duration cultivar 69–101 produced greater yield than the short duration cultivar TS 32‐1. The CROPGRO‐peanut model was able to predict and simulate the observed crop and pod dry matter over time when input on percent diseased leaf area and percent defoliation were provided. Of several disease assessments, the best approach was to input measured percent main‐stem defoliation above the fourth node and percent diseased leaf area estimated from visual leafspot score.