Climatic potential for winter wheat yield in Russia

The potential of crop yields illustrates the possibilities of increasing their production in the future. Modeling of potential yield of winter wheat on the European part of Russia was conducted based on specially developed GIS and the WOFOST crop growth simulation model. It was found that the winter wheat yield for Russia in general can be increased by 70% in the modern climatic conditions. The maximal potential for yield increasing was found in the regions situated on the Northern edge of the crop cultivation. In the Northern Caucasus, real crop yield is close to the climatic maximum; however, due to large crop acreage in Krasnodar krai, Stavropol krai, and Rostov and Volgograd oblasts, wheat harvest in each region can still be increased by 1–3 mln tons in each of them.     

冬小麦地膜覆盖的水分效应

在西北半干旱雨养条件下,采取3种地膜覆盖方式,研究了冬小麦地膜覆盖的水分效应.结果表明:覆膜可显著提高土壤表层(0～20 cm)墒情,越冬前至返青期覆膜处理的土壤表层含水量较露地处理(CK)高2.8%～6.4%,但拔节后覆膜处理的土层表墒与露地处理相近,而20 cm以下深层墒情则表现为覆膜处理逐渐低于露地处理;拔节至成...     

Improving in-season estimation of rice yield potential and responsiveness to topdressing nitrogen application with Crop Circle active crop canopy sensor

In-season site-specific nitrogen (N) management is a promising strategy to improve crop N use efficiency and reduce risks of environmental contamination. To successfully implement such precision management strategies, it is important to accurately estimate yield potential without additional topdressing N application (YP₀) as well as precisely assess the responsiveness to additional N application (RI) during the growing season. Previous research has mainly used normalized difference vegetation index (NDVI) or ratio vegetation index (RVI) obtained from GreenSeeker active crop canopy sensor with two fixed bands in red and near-infrared (NIR) spectrums to estimate these two parameters. The development of three-band Crop Circle active sensor provides a potential to improve in-season estimation of YP₀ and RI. The objectives of this study were twofold: (1) identify important vegetation indices obtained from Crop Circle ACS-470 sensor for estimating rice YP₀ and RI; and (2) evaluate their potential improvements over GreenSeeker NDVI and RVI. Four site-years of field N rate experiments were conducted in 2012 and 2013 at the Jiansanjiang Experiment Station of China Agricultural University located in Northeast China. The GreenSeeker and Crop Circle ACS-470 active canopy sensor with green, red edge, and NIR bands were used to collect rice canopy reflectance data at different key growth stages. The results indicated that both the GreenSeeker (best R² = 0.66 and 0.70, respectively) and Crop Circle (best R² = 0.71 and 0.77, respectively) sensors worked well for estimating YP₀ and RI at the stem elongation stage. At the booting stage, Crop Circle red edge optimized soil adjusted vegetation index (REOSAVI, R² = 0.82) and green ratio vegetation index (R² = 0.73) explained 26 and 22 % more variability in YP₀ and RI, respectively, than GreenSeeker NDVI or RVI. At the heading stage, the GreenSeeker sensor indices became saturated and consequently could not be used for YP₀ or RI estimation, while Crop Circle REOSAVI and normalized green index could still explain more than 70 % of YP₀ and RI variability. It is concluded that both sensors performed similarly at the stem elongation stage, but significantly better results were obtained by the Crop Circle sensor at the booting and heading stages. Furthermore, the results revealed that Crop Circle green band-based vegetation indices performed well for RI estimation while the red edge-based vegetation indices were the best for estimating YP₀ at later growth stages.     

Use of soil moisture data for refined GreenSeeker sensor based nitrogen recommendations in winter wheat (Triticum aestivum L.)

Previous studies have shown the importance of soil moisture (SM) in estimating crop yield potential (YP). The sensor based nitrogen (N) rate calculator (SBNRC) developed by Oklahoma State University utilizes the Normalized Difference Vegetation Index (NDVI) and the in-season estimated yield (INSEY) as the estimate of biomass to assess YP and to generate N recommendations based on estimated crop need. The objective was to investigate whether including the SM parameter into SBNRC could help to increase the accuracy of YP prediction and improve N rate recommendations. Two experimental sites (Lahoma and Perkins) in Oklahoma were established in 2006/07 and 2007/08. Wheat spectral reflectance was measured using a GreenSeeker? 505 hand-held optical sensor (N-Tech Industries, Ukiah, CA). Soil–water content measured with matric potential 229-L sensors (Campbell Scientific, Logan, UT) was used to determine volumetric water content and fractional water index. The relationships between NDVI, INSEY and SM indices at planting and sensing at 5, 25, 60 and 75-cm depths versus grain yield (GY) were evaluated. Wheat GY, NDVI at Feekes 5 and soil WC at planting and as sensed at three depths were also analyzed for eight consecutive growing seasons (1999–2006) for Lahoma. Incorporation of SM into NDVI and INSEY calculations resulted in equally good prediction of wheat GY for all site-years. This indicates that NDVI alone was able to account for the lack of SM information and thus lower crop YP. Soil moisture data, especially at the time of sensing at the 5-cm depth could assist in refining winter wheat YP prediction.     

温度及土壤含水量对冬小麦生长习性及返青率的影响

以抗寒性不同的冬小麦品种"东农冬麦1号"和"济麦22"为试验材料,研究土壤含水量及低温交叉逆境下两个材料的生长习性及返青情况。结果表明,生长习性与温度及土壤含水量无关,在不同温度及不同土壤含水量下东农冬麦1号植株均匍匐于地面生长,济麦22均直立于地面生长;返青率与土壤含水量及温度直接相关,含水量在25%左右最适于返青,随着经历低温时间的延长及温度的降低,返青率略有下降,幅度在60%~100%。在一定幅度范围内,温度与返青率呈极显著正相关,含水量与返青率呈负相关。研究结果可为指导大田冬小麦封冻前及春季返青前浇灌提供理论依据。     

伏旱与土壤湿度对春玉米和冬小麦产量的影响

利用甘肃省庆阳市黄土高原8个气象站1971—2018年共48年伏期降水量资料,分析了伏期降水和伏旱的空间分布特征、伏期降水的时间变化规律以及伏旱与春玉米和次年冬小麦产量的关系,用以代表黄土高原塬区董志塬上的西峰农业气象试验站1994—2018年春玉米田和1986—2015年冬小麦田伏期土壤相对湿度资料,分析了伏期土壤相对湿度与春玉米和冬小麦产量等的关系。结果表明,伏期降水量最少的是镇原气象站,为123.7 mm,次少的是环县气象站,为125.3 mm,最多的是正宁气象站,为162.5 mm,次多的是华池气象站,为149.9 mm。伏期降水量由东向西递减。伏旱频率最高的是合水、庆城、华池,为41.7%,伏旱频率最低的是宁县,为31.1%,频率从东北向西南递减。伏期降水量20世纪70年代降水偏少,80、90年代偏多,21世纪头10年偏少,2011—2018年偏多。伏期多雨年份比伏旱年份春玉米平均单产高960.0 kg/hm2;冬小麦平均单产高1 599.0 kg/hm2。伏期土壤相对湿度大年比小年玉米平均单产高2 287.5 kg/hm2;冬小麦平均单产高705.5 kg/hm2。     

气候变化对沧州地区冬小麦产量潜力的影响

本研究利用DSSAT V4.5模型模拟近50年来沧州地区冬小麦光温生产潜力、气候生产潜力及其在实际水肥条件下可获得产量的变化情况,分析沧州地区近50年的气候变化特征及气候变化对冬小麦产量潜力的影响,旨在为分析气候变化对黄淮海平原冬小麦生产系统的影响提供方法和思路。结果表明:1)近50年来沧州地区冬小麦生育期内平均温度呈极显著上升趋势,平均日照时数和太阳辐射呈减少趋势,平均降雨量呈不显著减少趋势,但降雨分布发生了季节性转移。2)冬小麦的光温生产潜力近50年呈减少趋势,平均每年减少17.94kg/hm2;气候生产潜力和可获得产量均呈增长趋势,平均每年分别增长31.02和3.62kg/hm2;实际产量呈极显著增长趋势,平均每年增长100.85kg/hm2。3)光温生产潜力和气候生产潜力之间的产量差呈不显著减少趋势,气候生产潜力和可获得产量之间的产量差呈不显著增长趋势,可获得产量和实际产量之间的产量差呈极显著减少趋势。4)气候因素的变化对冬小麦的生长和产量产生了明显影响,其中温度增加对冬小麦生长影响较为复杂,不同时期温度变化对冬小麦生长影响不同,总体呈负面影响;平均日照时数和太阳辐射的减少是冬小麦产量潜力降低的主要原因;平均降雨量的变化对冬小麦生长有利,气候变化的综合影响使冬小麦的生育期极显著缩短,开花期和成熟期极显著提前。因此,气候变化对沧州地区冬小麦的生产和产量潜力影响具有一定的复杂性,可以通过优化水肥管理措施来抵消气候变化产生的负效应。     

Assessing the potential of an algorithm based on mean climatic data to predict wheat yield

The real-time non-invasive determination of crop biomass and yield prediction is one of the major challenges in agriculture. An interesting approach lies in using process-based crop yield models in combination with real-time monitoring of the input climatic data of these models, but unknown future weather remains the main obstacle to reliable yield prediction. Since accurate weather forecasts can be made only a short time in advance, much information can be derived from analyzing past weather data. This paper presents a methodology that addresses the problem of unknown future weather by using a daily mean climatic database, based exclusively on available past measurements. It involves building climate matrix ensembles, combining different time ranges of projected mean climate data and real measured weather data originating from the historical database or from real-time measurements performed in the field. Used as an input for the STICS crop model, the datasets thus computed were used to perform statistical within-season biomass and yield prediction. This work demonstrated that a reliable predictive delay of 3–4 weeks could be obtained. In combination with a local micrometeorological station that monitors climate data in real-time, the approach also enabled us to (i) predict potential yield at the local level, (ii) detect stress occurrence and (iii) quantify yield loss (or gain) drawing on real monitored climatic conditions of the previous few days.     

旱作地膜覆盖穴播小麦底墒与产量关系

地膜覆盖穴播栽培技术是旱地小麦实现优质、高产稳产的有效途径。研究结果表明 ,地膜覆盖穴播小麦产量高低与土壤底墒关系密切。在旱地应用该技术时要因夏闲期降水多少和底墒状况而定。夏闲期降水多、底墒好的年份可采用该技术 ;夏闲期降水少、底墒差的年份会出现增产不增收的结果     

Lodging resistance and yield potential of winter wheat: effect of planting density and genotype

Improved lodging resistance is important for achieving high yield in irrigated environments. This study was conducted to determine genotypic variation in lodging resistance and related morphological traits among winter wheat cultivars planted at two densities, and to identify key traits associated with lodging resistance. Lodging performance of 28 genotypes, including 24 released cultivars and four advanced lines, was evaluated at 250 plants per square meter and 500 plants per square meter in Shandong province during the 2008–2009 and 2009–2010 crop seasons. At the higher density, the average grain yield was 2.6% higher, even though lodging score rose by as much as 136%. The higher planting density increased lodging through increased leaf area index (LAI), plant height, center of gravity and length of basal internodes, and reduced grain weight per spike and diameter of the lower two stem internodes. LAI, center of gravity and diameter of first internodes, as the important indicators for lodging resistance, were significantly correlated with lodging score, with R= 0.62, 0.59 and −0.52 (P<0.01), respectively. Plant pushing resistance was significantly associated with diameter and length of the first internodes (R = 0.71–0.77, P<0.01), indicating it could be used to assess the strength of the lower stem. Higher planting density could be used to select genotypes with lodging resistance in irrigated environments. Cultivars carrying high plant density tolerance and high yield potential, such as Jimai 22 and Liangxing 66, were recommended as leading cultivars for production as well as elite crossing parents for further increasing yield potential in the Yellow and Huai Valleys Winter Wheat Zone in China.     

塑料暗管排降条件下麦田土壤水分变化规律模拟

应用非饱和土壤水分运动原理，对塑料暗管排水条件下分层土壤的水分运动进行了数值模拟，建立了数学模型。结果表明，模型计算的土壤水分分布结果和田间实测的土壤部面水分数据一致，应用该模型可以确定出试验区在一定外界气象条件下不同地下水降落速度时农田的受渍情况。     

秸秆覆盖对旱地土壤水分及冬小麦水分利用效率的影响

【目的】研究秸秆覆盖方式与覆盖量对冬小麦田土壤水分及冬小麦产量和水分利用效率的影响。【方法】在陕西渭北旱塬,通过连续2年(2007-2009)的不同秸秆覆盖方式(全程覆盖、生育期覆盖、不覆盖(CK)与不同覆盖量(9000,6000,3000kg/hm2)的大田试验,研究秸秆覆盖对土壤水分及冬小麦产量和水分利用效率的影响。【结果】2年的定位试验结果表明,同一覆盖方式不同覆盖量处理的土壤含水量与覆盖量呈正相关;同一覆盖量不同覆盖方式下土壤含水量表现为全程覆盖优于生育期覆盖和CK;全程覆盖方式9000,6000和3000kg/hm2覆盖量处理0～200cm土层平均含水量较生育期覆盖分别提高了11.5%,10.0%和8.0%,较CK分别提高了19.2%,12.9%和8.8%;全程覆盖方式和生育期覆盖方式下,小麦的水分利用效率均以覆盖量为3000kg/hm2处理最大,其中全程覆盖方式的水分利用效率较CK增加了31.5%(P0.05),生育期覆盖方式下2年平均的水分利用效率较CK增加了12.8%(P0.05);不同覆盖量在全程覆盖方式下冬小麦产量较CK增加41.1%～65.7%(P0.05),在生育期覆盖方式下冬小麦产量较CK增加了27.1%～30.2%(P0.05)。【结论】同一秸秆覆盖方式不同覆盖量均可增加冬小麦产量,而同一覆盖量下以全程覆盖方式的增产效果较优;覆盖量为3000kg/hm2时,2种覆盖方式的冬小麦水分利用效率均最大。     

麦业丰对滨海盐碱地覆膜冬小麦生长及产量的效应

麦业丰对滨海盐碱地覆膜冬小麦地上部第 1和第 2节间伸长有明显的抑制作用 ,可使小麦地上部高度降低 ,茎秆更加粗壮 ,抗倒伏能力增强。与对照相比 ,单株黄叶数明显减少 ,单株叶面积增加 ,产量显著提高。     

冬小麦遥感估产多种模型研究

综合冬小麦地面光谱资料及相应的农学参数资料,ＮＯＡＡ／ＡＶＨＲＲ 资料,历年各县冬小麦单产、播种面积、总产资料,历年新疆各站气象资料,监测点历年冬小麦发育期、密度、产量分析等资料,证明地面光谱植被指数与冬小麦密度、生物量、叶面积指数关系密切,从而建立了密度与生物量的光谱监测模型,进而建立了北疆试验区各层冬小麦种植面积估算和产量预报卫星遥感模型,辅以冬小麦产量农业气象预报模型、农学模型及模拟模型,自１９９４ 年投入应用以来的结果表明,这套模型预报精度高、效果很好     

黄淮北片冬小麦区试产量性状的非参数度量

应用秩次参量nij和nij′ ,非参数统计量Pi、Pi′、Si 和Dj 描述 2 0 0 1～ 2 0 0 2年度黄淮北片冬小麦区试参试品系的基本特征 ,研究结果表明 :V8是丰产性最佳品系 ,产量稳定性最好的是V12 、V8、V2 、V3 ,表现丰产、稳产 ,对品系差异有较高分辨率的试点有 8个 ,分辨力最低的是L2 ,仅发现 2 2 2 %的差数为显著。     

不同灌溉梯度下冬小麦冠层温度与土壤水分关系研究

[目的]冠层温度是作物响应水分胁迫的重要指标,厘清小麦种植过程中冠层温度与土壤水分、周围环境因子之间的相互作用关系,对干旱监测、精准灌溉、智慧农业的发展有重要意义.[方法]文章采用温室试验,通过自动连续观测土壤含水量、作物冠层温度、环境因子,分析小麦拔节期在不同水分处理下冠层温度和土壤含水量的关系.[结果](1)小麦拔...     

稻麦秸秆全量还田对作物产量和土壤的影响

秸秆还田在农业生产中被普遍应用,对秸秆还田的作用已有不少研究[2～5 ].但较多报道论及的秸秆还田量一般较少,为秸秆总量的1/3～1/2.目前农作物秸秆作为燃料、垫料等应用在减少,秸秆焚烧、丢弃现象日益严重,既浪费有机肥资源,又污染环境.     

不同秸秆还田量对旱地土壤水肥和玉米生长与产量的影响

以阜新地区为例,开展不同秸秆还田量对旱地土壤水肥和玉米生长与产量的影响研究。试验设计0 kg·hm^-2,6 000 kg·hm^-2,12 000 kg·hm^-2,18 000 kg·hm^-2、24 000 kg·hm^-2共5个处理,3次重复,共15个小区,小区面积(4 m×15 m)为60 m²。研究结果表明,对照CK不施用秸秆处理,深耕加秸秆的方法,土壤含水量显著增加,除了对照之外,各个处理剂量之间的差异并不明显,且呈先上升而后下降趋势。说明秸秆在土壤中始终处于水分的非饱和状态,并不是秸秆剂量越大越好。各个层次土壤容重与对照相比变化较明显,其中10～20 cm深处土壤容重变化最大,各个处理土壤容重表现出随秸秆还田量增加土壤容重降低值减少的趋势,下降幅度为12 000 kg·hm^-2>6 000 kg·hm^-2>18 000 kg·hm^-2。秸秆还田处理,提高了植物的叶绿素含量,促进了植物的光合效率,以12 000 kg·h m^-2处理较好。不同处理对玉米产量影响差异显著,达到了5%的显著水平,施入量在0～12 000 kg·hm^-2之间,玉米产量呈上升趋势,超过18 000 kg·hm^-2产量呈下降趋势,因此建议推广剂量为12 000 kg·hm^-2。     

Evaluation of mid-season sensor based nitrogen fertilizer recommendations for winter wheat using different estimates of yield potential

Optical sensors, coupled with mathematical algorithms, have proven effective at determining more accurate mid-season nitrogen (N) fertilizer recommendations in winter wheat. One parameter required in making these recommendations is in-season grain yield potential at the time of sensing. Four algorithms, with different methods for determining grain yield potential, were evaluated for effectiveness to predict final grain yield and the agronomic optimum N rate (AONR) at 34 site-years. The current N fertilizer optimization algorithm (CNFOA) outperformed the other three algorithms at predicting yield potential with no added N and yield potential with added N (R² = 0.46 and 0.25, respectively). However, no differences were observed in the amount of variability accounted for among all four algorithms in regards to predicting the AONR. Differences were observed in that the CNFOA and proposed N fertilizer optimization algorithm (PNFOA), under predicted the AONR at approximately 75 % of the site-years; whereas, the generalized algorithm (GA) and modified generalized algorithm (MGA) recommended N rates under the AONR at about 50 % of the site-years. The PNFOA was able to determine N rate recommendations within 20 kg N ha^?1 of the AONR for half of the site-years; whereas, the other three algorithms were only able recommend within 20 kg N ha^?1 of the AONR for about 40 % of the site-years. Lastly, all four algorithms reported more accurate N rate recommendations compared to non-sensor based methodologies and can more precisely account for the year to year variability in grain yields due to environment.     

Independence of yield potential and crop nitrogen response

Crop yield level and nitrogen (N) responsiveness influence the demand for fertilizer. If they were found to be unrelated, this would justify using a combination of both for determining fertilizer N requirements. Failure to understand the independence of crop response to N and yield level has led to confusion as to what theory is appropriate for making N fertilizer rate recommendations. The sufficiency approach applies a fixed rate of N at a computed sufficiency level, regardless of yield potential. Alternatively, mid-season optical sensor estimates of yield potential and crop response to additional N provide a physiological basis to estimate N removal and a biologically based N application rate. This study investigated the relationship between grain yield and response to N in long-term wheat and corn experiments. No relationship between response to N and grain yield was found. There was also no relationship between yield and year at two of three sites. Finally, there was no relationship between response to N and year at any site. Because yield and response to N were consistently independent of one another, and as both affect the demand for fertilizer N, estimates of both should be combined to calculate realistic in-season N rates.