水稻免耕栽培的减灾效应研究

为探索稻田保护性耕作技术——水稻免耕的减灾效应,将免耕与传统稻作方法相结合组成常耕移栽、常耕抛秧、免耕移栽、免耕抛秧4个处理进行试验,并运用生态学原理对试验结果进行了分析研究。结果表明,稻田保护性耕作能提高作物产量,降低部分生育期间水稻病虫害,抑制农田杂草的生长。     

气候变暖对龙口小麦适播期的影响

在目前气候明显变暖情况下,以往总结确定的冬小麦播期指标理应做相应调整。通过理论计算得出龙口市小麦最佳播期是：精播栽培期为10月1-9日,中播栽培期为10-18日,独秆栽培期为19-29日。通过3年的试验证明,10月5,10日播种比9月25日和10月1日播种更适宜,不仅能避免过旺生长,而且显著减少了根腐病、纹枯病发病率,小麦表现高产稳产。     

秋季低温对南召县水稻生产的影响及防御对策

秋季低温对南召县水稻生产的影响主要是显著降低结实率和产量.对水稻生理机制及品种、播期等分析结果表明,迟播、品种、密播、裁插过稀、偏施氮肥及土质较差,是秋季低温导致水稻减产的主要原因.因此,采取地膜覆盖早育秧、适当早播、合理选用品种、足肥稀播、合理密植、平衡施肥及喷施激素等措施,可减轻其危害程度,促进南召水稻生产可持续发展.     

宝鸡光热水气候因素对玉米生产的影响分析

运用积分回归方法,对宝鸡地区的眉县、风翔和麟游3个代表县1981--2010年30a玉米产量与气象因子进行了分析。结果表明：播种期干旱和灌浆期低温阴雨寡照对夏玉米的影响程度塬区大于川道;春旱和初夏早是制约山区春玉米产量的主要因素。适时早播,利用前期的热量避免后期低温阴雨寡照,对宝鸡玉米生产尤为重要。通过改善品种,强化管理．可以有效降低不利气象因素对川塬夏玉米种植区生产的影响;发展地膜覆盖栽培将是解决不利气象条件对山区春玉米种植区影响的主要方法。     

高寒区马铃薯地膜覆盖增温与增产效应

通过在青海省高寒农业区(海拔2700—3000m)的马铃薯地膜覆盖丰产栽培试验,着重分析了高寒农业区地膜覆盖的增温效应对马铃薯产量的影响及马铃薯产量与气象条件的关系等。并阐述了高寒区马铃薯地膜覆盖栽培适宜推广的范围。     

陆川县冬种马铃薯生产中瓶颈问题的气象探索

对陆川县主栽的马铃薯品种黑龙江K3紫花,采用稻草免耕栽培措施分四次播种进行试验,对试验中造成马铃薯的出苗期烂种、生长后期晚疫病等原因的气象条件进行分析,并探索解决的方法。     

播期对不同类型水稻生长及产量构成因素的影响

通过分期播种,研究了不同播期对水稻生长和产量的影响.通过测定不同播期水稻抽穗期和成熟期的叶绿素、可溶性糖和氮的质量分数,分析不同播期对水稻生长的影响.结果表明Ⅰ期为两优培九和6两优9386最适宜播期,Ⅱ期为Ⅱ优084最适宜播期.播期对水稻单株穗数、每穗粒数、结实率、千粒重均有影响,尤其是对两优培九的结实率、6两优9386的每穗粒数有显著影响.研究结果可为合理利用南方气候资源、合理安排播栽播期、提高水稻产量提供理论依据和技术指导.     

不同播期的优质小麦产量结构分析

对不同优质小麦品种不同播期的产量结构分析结果表明:河北-8901的各种产量结构表现出最为稳定的变化规律,即不同的播期处理对最后产量的影响度相对较小;郑麦-9405和郑麦-9023的产量结构在不同的播期表现出较大的波动。     

不同播期的优质小麦产量结构分析

对不同优质小麦品种不同播期的产量结构分析结果表明：河北-8901的各种产量结构表现出最为稳定的变化规律，即不同的播期处理对最后产量的影响度相对较小；郑麦-9405和郑麦-9023的产量结构在不同的播期表现出较大的波动。     

气候生产潜力的季节分配与玉米的最佳播期

本文将气候生产潜力划分为三个层次,即光能生产潜力、光温生产潜力和光温水生产潜力。应用基于供水量与需水量之比建立的光温水生产潜力,计算了北京地区不同播种期的玉米可能产量,得出明显的峰状曲线,其峰值及其相应的播种期即最佳播期均与栽培试验的结论非常一致,这表明气候生产潜力的理论可为农学中的适宜播期问题建立理论基础。     

北方冬小麦冬季冻害及播期延迟应对

全球变暖背景下, 我国北方冬麦区冬季冻害是否仍是主要气象灾害,冬小麦播期延迟是否能作为应对气候变化的措施,成为当前亟待解决的科学问题。研究表明:1981—2000年北方冬麦区偏北地区冬季冻害指数与冬小麦减产率相关系数为0.62(达到0.001显著性水平),即2000年前冬季冻害是冬小麦减产的主要气象灾害之一;2000年后冻害与冬小麦减产率相关不显著,即冬季冻害已不再是冬小麦减产的主要影响因子。2018—2021年的冬小麦分期播种试验分析表明:山东泰安和陕西咸阳主栽的冬小麦品种播期推迟,冬前积温和生长季积温明显减少,导致冬小麦植株高度、地上总干重和叶面积指数减小;播期推迟对产量结构造成不利影响,有效穗数、穗粒数和千粒重均分别减少,导致减产,播期推迟10 d平均减产22%,推迟20 d平均减产40%。因此,冬小麦推迟播期并未产生积极效应, 可能原因是当前冬小麦播期和主栽的冬小麦品种已适应当地气候变化。     

基于分期播种试验的小麦越冬前适宜指标探讨

基于2006-2007和2007-2008年度郑麦366的分期播种试验资料,结合郑州农业气象试验站多年同品种小麦业务观测资料,利用相关分析、最小显著差数等方法,对越冬前积温、小麦生长状况及产量构成进行了分析,结果表明：冬小麦越冬前的生长状况与各发育阶段积温有很强的相关性,产量构成的三要素也与越冬前各发育阶段积温及分蘖数...     

基于WOFOST模型的辽西地区典型旱年不同播期玉米干旱损失评估

针对干旱灾害频发的辽西地区, 以春玉米为研究对象, 选取WOFOST作物模型, 利用干旱胁迫控制试验数据、田间试验数据和气象数据驱动模型, 进行典型旱年的模型适用性及不同播期的干旱损失评估研究。结果表明: 经过参数校准后的WOFOST模型能够较好的模拟辽西地区典型旱年春玉米产量及损失。辽西地区不同播期受干旱的影响程度不同, 因旱减产风险随播期推迟而减小, 2015年(中旱)干旱导致的平均减产率可达59%—61%, 2018年(轻旱)可达20%—39%, 2020年(中旱)可达36%—62%。不同生育期内干旱对产量的影响程度不同, 总体上拔节期—抽雄期和抽雄期—乳熟期持续重旱对产量的影响最大, 其次是抽雄期—乳熟期、拔节期—抽雄期。玉米各生育期受干旱影响程度, 朝阳站最大, 其次是黑山站和阜新站。辽西地区在旱年, 拔节期—抽雄期发生中旱和重旱风险随播期推迟而增加, 抽雄期—乳熟期发生中旱和重旱风险随播期推迟而减少, 当拔节期—抽雄期和抽雄期—乳熟期连续发生重旱, 干旱灾损程度随播期推迟而加重, 减产率可高达46%—84%。     

膜下条播冬麦栽培技术的进一步探讨

膜下条播冬麦栽培技术是夺取旱地小麦和晚播小麦高产的一项突破性新技术,加之一次完成播种、铺膜一条龙播种机的配套高效作业,其增产显著。从膜下条播冬麦栽培技术在地区中试和示范3a来,使小麦生产上一个新台阶。     

海拔2800m的山区地膜春小麦试验研究

2006年,在海拔2800m以上的和田县喀什塔什乡科克阿依村进行地膜穴播春小麦与露地春小麦栽培对比试验。地膜覆盖技术改善了小麦生物性状,分蘖数和成穗率大大提高,千粒重也有所增加。除4月15日播种的外,株高、结实小穗数、穗粒数都比露地播种小麦增加,A、B、C三处理比对照籽粒产量分别增加75．5％、82．0％和52.3％,增产效果非常明显。能有效解决低温半干旱山区春小麦生产中存在的粗、旱、冻等突出问题,具有较好的保墒蓄水、增温保温效能,有明显的增产增收作用,是小麦生产再上台阶的一项有力措施,值得在南疆海拔2800m以上的山区大力推广应用。     

Assessing Winter Wheat Responses to Climate Change Scenarios: A Simulation Study in the U.S. Great Plains

Hard red winter wheat (Triticum aestivum L.) is a major crop in the Great Plains region of the U.S. The goal of this assessment effort was to investigate the influence of two contrasting global climate change projections (U.K. Hadley Center for Climate Prediction and Research and Canadian Centre for Climate Modelling and Analysis) on the yield and percent kernel nitrogen content of winter wheat at three locations in Nebraska. These three locations represent sub-humid and semi arid areas and the transition between these areas and are also representative of major portions of the winter wheat growing areas of the central Great Plains. Climate scenarios based on each of the projections for each location were developed using the LARS-WG weather generator along with data from automated weather stations. CERES-Wheat was used to simulate the responses for two contrasting cultivars of wheat using two sowing dates. The first sowing date represented current sowing dates appropriate for each location. The second sowing date was later and represents the approximate date when the mean air temperature from the climate scenarios is the same as the mean air temperature from the actual climate data at the current sowing dates. The yield and percent kernel nitrogen content using the two climate scenarios generally decrease going from the sub-humid eastern to the semi arid western parts of Nebraska. Results from these simulations indicate that yield and percent kernel nitrogen content using the two climate scenarios could not both be maintained at levels currently simulated. Protein content (directly related to kernel nitrogen content) and end-use quality are the primary determinants for the use of hard red winter wheat in baked goods. Nitrogen management and new cultivars, which can enhance the uptake and translocation of nitrogen, will be proactive steps to meet the challenges of global climate change as represented by these climate scenarios.     

Yield estimation and sowing date optimization based on seasonal climate information in the three CLARIS sites

The present article is a contribution to the CLARIS WorkPackage “Climate and Agriculture”, and aims at testing whether it is possible to predict yields and optimal sowing dates using seasonal climate information at three sites (Pergamino, Marcos Juarez and Anguil) which are representative of different climate and soil conditions in Argentina. Considering that we focus on the use of climate information only, and that official long time yield series are not always reliable and often influenced by both climate and technology changes, we decided to build a dataset with yields simulated by the DSSAT (Decision Support System for Agrotechnology Transfer) crop model, already calibrated in the selected three sites and for the two crops of interest (maize and soybean). We simulated yields for three different sowing dates for each crop in each of the three sites. Also considering that seasonal forecasts have a higher skill when using the 3-month average precipitation and temperature forecasts, and that regional climate change scenarios present less uncertainty at similar temporal scales, we decided to focus our analysis on the use of quarterly precipitation and temperature averages, measured at the three sites during the crop cycle. This type of information is used as input (predictand) for non-linear statistical methods (Multivariate Adaptive Regression Splines, MARS; and classification trees) in order to predict yields and their dependency to the chosen sowing date. MARS models show that the most valuable information to predict yield amplitude is the 3-month average precipitation around flowering. Classification trees are used to estimate whether climate information can be used to infer an optimal sowing date in order to optimize yields. In order to simplify the problem, we set a default sowing date (the most representative for the crop and the site) and compare the yield amplitudes between such a default date and possible alternative dates sometimes used by farmers. Above normal average temperatures at the beginning and the end of the crop cycle lead to respectively later and earlier optimal sowing. Using this classification, yields can be potentially improved by changing sowing date for maize but it is more limited for soybean. More generally, the sites and crops which have more variable yields are also the ones for which the proposed methodology is the most efficient. However, a full evaluation of the accuracy of seasonal forecasts should be the next step before confirming the reliability of this methodology under real conditions.     

1960—2017年沈阳地区春播期降水变化特征

基于1960—2017年沈阳市5个气象观测站4—5月降水量资料,采用线性趋势法和累积距平分析了沈阳市春播期(4—5月)降水量演变特征,并分析首场透雨及最大连续无有效降水日数演变特征及对春播期降水量影响,对春播期降水量资源变化特征进行相关分析。结果表明:近58a沈阳春播期降水量整体呈现弱的增加趋势,平均每10a增加3.1mm,2004年开始降水量迅速增加,且波动性较大,降水量异常偏多或偏少年份较多,易诱发春旱春涝事件。春播期首场透雨出现日期平均每10a偏晚0.051d,首场透雨日期偏晚,将导致春播期前期雨水条件不足,引起土壤干旱,不利于春播开展。最大连续无有效降水日数呈波动性增加趋势,平均每10a增加0.56d,对4月降水量影响较大,虽然春播期降水资源总量增加,但存在降水资源时间分配不均的问题,且长时间无有效降水事件频发,将导致春播期干旱灾害事件发生风险加大,导致适播期延后。     

气候变化对我国江南双季稻生产可能影响的数值模拟研究

在利用田间试验资料对双季稻生长动力（态）模拟模型进行验证的基础上,将基于GCMs的输出和历史气候资料相结合的气候变化情景与双季稻模式相连接,就气候变暖对我国江南双季稻主产区水稻生产的可能影响进行网格化定量模拟和客观评估,并就调整对策（改变播种日期和种植品种）在减缓气候变暖对双季稻生产影响中的作用作了初步的探讨。结果表明,在未来可能的气候变化情景下,若维持目前的品种和生产技术措施,双季稻产量将有不同程度的下降。产量变化的地域分布既有一定的规律性,又体现出气候变化影响的复杂性。适应对策分析表明,改种长生育期的     

Analysis of the climatic constraints to maize production in the current agricultural region of Argentina—a probabilistic approach

A simple method of analysis was proposed to characterize the impact of climatic conditions of a wide region of Argentina (from 27°05′S to 35°48′S, from 61°5′W to 64°21′W) on potential maize (Zea mays L.) grain yield, and the occurrence of various climatic constraints (low temperatures and low soil water content, frost, drought stress and heat stress) along the cycle. The analysis was based on previous studies of the eco-physiology of maize crops and the use of climatic records of six locations in the region under study. Results were analyzed using a probabilistic method, later organized as a checklist to consider when deciding on sowing date in a location of the region. Thus, for each production scenario (combination of location and sowing date), farmers would have a tool enabling them to pay particular attention to the restrictions more likely to occur, to include some cultural practices to avoid or mitigate the most severe climatic constraint to maize production.