Comparative performance of winter and spring malting barleys in semiarid growing conditions

In Europe, during the 1960s, mainly two-rowed spring barley was used for malting. Traditionally, spring malting barley was produced in regions with moderate temperatures and adequate rainfall throughout the growing season. Winter malting barley, on the other hand, was mostly grown in the milder arid and semiarid parts of Europe. Due to global climatic changes and its higher yield, winter malting barley is now increasing in acreage in the traditional spring barley regions. Our study included a comparative analysis of several grain and malt characters of the winter and spring malting barley grown under the agroecological conditions of the Vojvodina Province, Yugoslavia. One thousand grain weight was shown to be approximately the same for both growth habits, whereas winter malting barley proved to have a higher hectoliter mass than the spring one. In those years that were less favorable for spring barley production, winter malting barley had better quality characters, namely a higher fine extract content, a better malt modification, and a lower malt protein content. This revised version was published online in July 2006 with corrections to the Cover Date.     

多参数冬小麦估产模型研究及产量影响因素分析

产量估算研究对制定粮食政策和经济计划,科学地进行粮食宏观调控有着重要意义。针对以往线性遥感估产模型中多是基于NDVI和LAI的研究,且参数间存在多重共线性等问题,该研究以河北省南部石家庄、保定、邯郸、邢台、衡水、沧州六市为研究区,选用2000—2008 年的种植区最佳时相NDVI、LAI累加值,并引入与小麦生物量积累密切相关的不同月份地表温度作为原始估产指标,针对参数累加值存在的误差,提出一个修正公式对NDVI、LAI 进行修正,再对选用参数进行主成分分析,将结果与冬小麦产量数据建立出4 个多参数综合作用的冬小麦遥感估产模型。结果表明,利用2009 年数据对模型进行验证,结果表明4 个模型的R2介于0.714~0.818 之间,估产精度均在93.0%以上,其中,综合所有遥感参数的模型拟合效果最好,R2为0.818,估产精度达95%,而且引入温差主成分的模型精度高于仅用NDVI、LAI作参数的模型,另外深入分析各参数对产量估测的影响可知4 月中旬和5 月中旬的地表昼夜温差对冬小麦的后期产量具有较大影响。     

锡林郭勒草地NDVI和牧草估产产量的变化特征

为及时准确了解草地牧草生长状况,利用EOS/MODIS遥感资料结合地面同步调查数据,分析锡林郭勒草原草甸草原、典型草原和荒漠草原3种草地类型NDVI和草地生物量的月际变化特征。结果表明,利用S曲线回归估产模型测算的草地生长季逐月牧草产量能较好地反映其生长状况变化,体现了各类草地地上生物量的分布特征。其中,草甸草原牧草生长季NDVI和牧草平均估产产量变化范围分别为0.208~0.560和39.8~168.6g/m²（干重）,峰值出现在8月;典型草原牧草生长季NDVI和牧草平均估产产量变化范围分别为0.194~0.480和33.7~146.2g/m²（干重）,峰值出现在7月;荒漠化草原牧草生长季NDVI和牧草平均估产产量变化范围分别为0.130~0.185和10.0~29.8g/m²（干重）,峰值出现在7月。     

Estimation of Leaf Area Index of Beta vulgaris L. Based on Optical Remote Sensing Data

Remote sensing and vegetation indices can be used to characterize the canopy of crops with a non‐destructive method on a large scale. Leaf area formation of sugar beet in early summer is the most important variable for crop growth models. This study aimed at estimating whether differences in leaf area development of sugar beet resulting from different agronomic practices can be determined with remote sensing. The relationship between the normalized difference vegetation index (NDVI) and leaf area index (LAI) during the season and yield of the storage root in autumn was studied in six field trials in 2001 and nine field trials in 2002. The vegetation index NDVI gave a good impression of differences in leaf development of sugar beet in early summer. LAI increased with increasing NDVI up to an NDVI of 0.65. Above that the NDVI did not respond as distinctly to treatments as the LAI. An exponential function was developed to calculate sugar beet LAI from NDVI, so that remote sensing data can be used as input variable for crop growth models. The yield of the storage root in autumn did not show any relationship to LAI or NDVI during the season, regardless of whether it was measured in June or September. Therefore, it seems to be necessary to combine NDVI data with crop growth models to forecast a potential sugar beet yield in autumn. For this purpose the formula presented is a valuable tool.     

NOAA卫星玉米遥感估产方法的研究

利用美国国家海洋大气总署卫星空间覆盖度宽，运行周期短，资料获取时次多的特点，通过光面光谱观测寻求玉米遥感估产最佳时相期，经过对ＰＶＩ理论推得出ｆ值，在ＲＶＩ混合象元中提取玉米长势信息，建立了河北省空间玉米遥感估产模式。经过三年的预报结果检验，误差小于５％。     

基于遥感信息与水稻模型相结合对镇江地区水稻种植面积与产量的估测

为了实现遥感信息与作物模型相结合对镇江地区的水稻种植面积与产量的估测,以便于可以直接利用遥感信息与模型对该地区的水稻生长进行监测,将遥感资料与水稻生产模型(ORYZA2000)相结合,建立遥感数值模拟模型,进行由点及面的区域水稻种植面积及产量的估测。利用遥感数据（8天合成的MODIS和环境小卫星数据）,计算归一化植被指数(NDVI)和增强植被指数(EVI),结合试验区实测的叶面积指数(LAI),建立植被指数与LAI之间的关系,通过模型模拟出的LAI计算出植被指数的浮动值,结合相对应的多时相的遥感数据识别镇江市的水稻,由此可以预报镇江市的水稻种植面积及产量。研究结果表明,模型对水稻生长发育期内的生物量和LAI的模拟较好,水稻LAI与遥感资料计算出的植被指数EVI的幂函数拟合性较好,可以应用这种相关模式识别水稻,并结合ORYZA2000模型提高区域范围的水稻估测精度,同时也体现了遥感信息与作物模型相结合可以很好的监测区域内水稻的生长情况,取得较好的模拟效果。     

氮素和小麦条锈病胁迫下小麦高光谱遥感估产模型研究

为了构建不同施氮水平和条锈病发病条件下的小麦估产模型,设置了不同氮素水平及人工接种小麦条锈病,通过采用将多个关键生育期的光谱植被指数、一阶微分参数与小麦条锈病病情指数、叶片含氮量、产量构成因子、产量进行相关分析,植被指数、一阶微分参数与产量进行回归分析的方法,研究与产量相关性高的植被指数、微分参数,结果表明分别利用绿光红光比值植被指数(GR)和绿光波段一阶微分值总和(SDg)、蓝光波段一阶微分值总和(SDb)在灌浆期构建的估产模型预测效果较好,2010年预测准确率分别可以达到99.87%、99.98%,2011年预测准确率分别可以达到97.9%和95%。通过试验研究发现高光谱遥感技术在氮素和小麦条锈病双重胁迫下也可以较好的预测产量,这对研究多重胁迫、多种栽培措施下的小麦估产模型有重要意义。     

不同基因型啤酒大麦冠层叶片光合特性对产量的影响

为给啤酒大麦高产栽培提供理论依据,采用便携式光合分析系统研究不同基因型啤酒大麦冠层叶片光合速率变化,分析其对产量的影响。研究结果表明,参试基因型中M-22（1）、KH LEDI（4）、Pasadena（15）、Z014J081J（19）、MERIT（20）、Z090M066M（25）等二棱大麦的叶面积指数(LAI)一直较高,其中以美国的新品种之一Z014J081J表现最为突出,平均LAI达2.69;不同基因型啤酒大麦叶面积指数阶段变化与产量呈现一定的正相关关系, 从挑旗期到灌浆末期整个生育阶段的LAI变化与产量的相关性均达到极显著水平;相关分析表明,不同基因型啤酒大麦冠层光合速率阶段变化与产量呈现一定的正相关关系。其中孕穗期、抽穗开花期和灌浆末期的光合速率变化与产量的相关性达极显著水平,相关系数分别为0.5024、0.5360和0.6758。     

遥感技术在烟草长势监测及估产中的应用进展

烟草长势信息是烟草生产管理的重要依据,全面了解遥感技术在烟草长势监测及估产中的应用进展,为利用遥感技术支撑科学化、精细化烟田管理提供科学参考。在对相关文献分析和归纳的基础上,从地面光谱、无人机遥感、卫星遥感3种尺度对目前遥感技术在烟草长势监测与估产方面的应用进行系统总结,并对进一步研究进行展望。（1）基于地面光谱对烟草的监测,主要是利用反射率光谱及其不同的变换形式、光谱指数和光谱位置变量估测其生理生化参量（氮、磷、钾、生物量、叶面积指数、叶绿素等）,为诊断烟草生长、健康状况、成熟度提供依据,进一步实现烟草长势监测、估产与品质评定。（2）利用无人机遥感技术能够在小尺度上对作物的面积进行提取、监测长势及估产,但受搭载相机分辨率、地形、自身稳定性等影响,不能监测烟草的细微变化。（3）参考LandSat、SPOT、MODIS、HJ-1等光学遥感数据以及SAR数据,利用遥感影像融合、分类等技术能够实现对大面积烟田病害、长势进行监测和产量估计。结合多源、多平台遥感数据,对烟草的参数进行定量研究,并利用同化技术对大尺度上烟草生长过程进行动态监测,来探索烟草的最佳采收期是未来研究的重点。     

玉米和大豆LAI高光谱遥感估算模型研究

以ASD FieldSpec光谱仪实测了不同生长季的大田玉米、大豆的冠层高光谱与作物的叶面积指数LAI。采用单变量线性与非线性拟合和逐步回归分析的方式,建立了玉米、大豆LAI高光谱遥感估算模型,并对模型的估算结果进行了初步分析。分析结果表明,绿光波段反射峰区、红光波段以及近红外区的单波段反射率与作物的LAI有较强的相关性,而其他波段的反射率与作物的LAI的相关性相对较弱;以高光谱的窄波段构造的NDVI和RVI与作物的LAI的相关程度高,回归模型的预测水平高;而以多波段逐步回归方式构造的统计模型的预测效果最好。     

遥感光谱技术在农作物产量估算中的应用研究进展

农作物产量是一个国家或地区的重要经济信息,关系着国家和区域粮食安全,对农业规划布局、政策调整及可持续发展等方面具有重要意义。农作物遥感估产主要包括作物识别和产量评估两项主要环节,文章通过总结农作物遥感识别与产量估算的研究现状,以其依据的特征不同、针对的目标不同对现有的作物识别分为两类进行总结；根据数据源与评估模型原理的区别将现有作物遥感估产方法总结为四类,对其方法、原理和应用要点进行总结,讨论分析了各类方法的优势和仍需完善的问题,并对今后的发展趋势进行了展望。     

基于遥感技术的沙坨草甸交错带玉米农业气象灾害评估——以科尔沁左翼后旗为例

为了评估农业气象灾害对沙坨草甸交错带玉米产量的影响,于2013 年灾后在科尔沁左翼后旗进行实地测产,结合遥感估产和生态分类的方法,以遥感图像数据为主,地面测试数据为辅,获取农作物受灾面积,进而对科尔沁左翼后旗玉米进行灾害评估。结果表明,科尔沁左翼后旗农业区各镇玉米地受气象灾害影响程度的大小顺序为：双胜镇＞金宝屯镇＞查日苏镇,其绝产面积分别达到669.87、55.23 和6.77 hm2。玉米产量受损主要受气象灾害影响,除此还与土壤类型、玉米生育期、地形地貌等因素有关。利用玉米长势衰减表现在光谱响应特征差异的特性,估测玉米不同受灾程度的受灾面积成为可能,对于农业上遥感估产具有非常重要的作用。     

基于ESTARFM模型的区域农田高时空分辨率影像产生与应用

多时相遥感影像特别是关键生育期数据是农业物候、长势及产量监测的重要数据源,然而可见光影像易受云雨干扰,在特定区域关键时间窗口缺少高时空分辨率数据的现实情况下,遥感影像时空数据融合方法变得尤为重要。增强型自适应反射率时空融合模型ESTARFM (Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model)是一种小区域合成高时空分辨率影像的较好方法,该算法在我国不同农业种植区的适应性及应用工作尚未充分展开。本文以河北、黑龙江、新疆典型农区为研究区域进行大面积应用检验分析,基于MODIS与Landsat影像,利用ESTARFM生成具有高时空特征的Landsat模拟影像,将其与真实Landsat影像进行对比,并在新疆地区展开ESTARFM算法在NDVI方面的应用。结果表明, ESTARFM对3个不同区域状况的地区都有较好的影像预测能力,并且在新疆地区可以很好地生成30 m空间分辨率的多时相NDVI,用于作物分类和长势监测。     

中国农作物长势遥感监测研究综述

农作物长势监测的目的是为早期估产提供依据，同时为田间管理提供及时的信息。笔者总结了中国农作物长势监测的研究进展、研究方法，指出用于长势监测的遥感数据空间分辨率较低，常用的监测指标 具有局限性，监测精度有待提高。“3S”技术的集成发展，进一步实现一体化应用于该领域仍是今后的发展方向。随着农作物长势运行化监测系统的进一步完善，对田间管理的诊断需求会日益加剧，因此作物长势的诊断将成为今后的研究重点。     

The EEC Barley and Malt Committee Index for the Evaluation of Malting Quality in Barley and its Use in Breeding

A new statistical quality index, Q, is defined in order to facilitate the interpretation of the overall quality of malting barley varieties. Q ranges from O (feeding barley) to 9 (top quality malting barley), and is related to the Normal distribution. The varieties tested within the network of the European Brewery Convention are assessed for malting quality as an example of tire reliability of Q. In addition, the new index is used to study the genotype X environmental interaction for malting quality.     

Effect of region on the uncertainty in crop variety trial programs with a reduced number of trials

Results from crop variety trials may vary between geographical regions because of differences in climate and soil types. Results are usually presented at regional level. To evaluate the importance of the regions used in the Swedish variety trial programs, we examined which regions produced similar levels of yield and similar ratios in yield between cultivars; the amount by which variance could be reduced by division into regions or clusters of regions; and the amount of trials per region and year, replicates per trial, and trials per year required in order to fulfill specifications on the precision of results. Yield data from spring barley and winter wheat trials performed during 1997–2006 were studied using cluster analysis and variance component estimation. The objectives were (1) to discuss the effects of regions on precision when the number of trials has decreased; (2) to demonstrate the method; and (3) to report the results obtained. In spring barley, clusters of regions produced different levels of yield, but similar yield ratios between cultivars. In winter wheat, clusters of regions giving different yield ratios were identified. When the option of a single analysis was compared with that of region-wise analysis, the reduction in variance with the former, due to the larger number of trials, outweighed the reduction in variance with the latter due to decreased random interaction between trials and cultivars.     

基于GreenSeeker的冬小麦NDVI分析与产量估算

以2007-2009年连续2个冬小麦生长季的田间试验数据为基础,利用GreenSeeker获取冠层归一化差值植被指数(NDVI),分别对不同氮营养条件下冬小麦的产量变化、冠层NDVI值随施氮量和生育期的动态变化,以及NDVI与产量的相关性定量分析,建立基于NDVI的冬小麦产量估算模型。结果表明,冬小麦的产量变化随施氮量的增加呈抛物线趋势变化;冠层NDVI在返青期前随施氮量增加基本不变,返青期至灌浆初期随施氮量增加呈显著增加趋势;整个生育期冠层NDVI呈现“低–高–低”变化趋势。冬小麦整个生育期不同施氮水平下的NDVI值与产量的相关性均为正相关关系,且相关性随生育期逐渐增强,在灌浆末期达到最大。利用NDVI建立的冬小麦产量估算模型,以灌浆初期(P=0.005)和灌浆末期(P<0.001)的模型达到极显著水平。经验证,灌浆初期的冬小麦产量预测值与实测值的回归关系达到了显著水平(P=0.0129),灌浆末期则达到极显著水平(P=0.0002)。因此,利用灌浆初期和灌浆末期的NDVI值可以预测冬小麦产量,尤以灌浆末期预测效果更佳。     

Relationships between Yield and Quality Parameters of Malting Barley (Hordeum vulgare L.) and Phenological and Meteorological Data

In this study, phenological and meteorological data have been used to interpret variations in a time series of regional average yields and quality parameters of malting barley (Hordeum vulgare L). The analyses were focused mainly on the grain filling period. Duration and occurrence of this development stage showed remarkable differences from year to year, as heading varied over more than four weeks and yellow ripeness over two weeks in the investigation period from 1974 to 1996. Yields above average were achieved only in years when grain filling duration exceeded 42 d. Protein concentrations below 10.5 % and grading percentages over 90 % required at least 44 d of grain filling. Temperature had the strongest influence on the length of grain filling, even though the calculated Growing Degree Days (base temperature 3 °C) were not absolutely constant. Mean daily temperature and relative air humidity were the best estimators with respect to grain yield. An optimum temperature range was found between 14 and 18 °C. Assuming a linear relationship, yield reductions between 4.1 and 5.7 % have been calculated for every 1 °C increase of the mean daily temperature. Relative air humidity was the best single estimator for grain protein concentration. The results of this study suggest that relative humidity during grain filling can be a more suitable parameter to describe drought stress effects than precipitation amounts from heading to yellow ripeness or from January 1 to yellow ripeness.     

基于气象适宜度指数的若尔盖湿地天然牧草产量估算模型

气象条件极大地制约着若尔盖湿地天然牧草的生长状况,为了从气候条件适宜角度评估牧草长势年景的优劣,利用若尔盖湿地天然草场牧草1983—2013年近31年(2002年缺测)牧草产量观测资料,得到能够反映光、温、水对牧草生长影响程度的气象适宜度指数,分析了若尔盖湿地天然牧草产量与气象因子之间的关系,分别建立了5月、6月和7月牧草产量气象适宜度线性和生长曲线估算模型。结果表明:所建立的牧草产量气象适宜度估算模型能够较好地模拟牧草产量的演变趋势;各月气象适宜度产量线性模型的精度普遍高于生长曲线模型;与干重模型相比,鲜重模型精度较差。受牧草产量观测资料精度的限制,6、7月牧草产量估算模型还需要进一步改进。     

Quantitative trait loci for grain yield and yield components in a cross between a six-rowed and a two-rowed barley

Summary The positions of quantitative trait loci (QTL) for yield and yield components were estimated using a 85-point linkage map and phenotype data from a F₁-derived doubled haploid (DH) population of barley. Yield and its components were recorded in two growing seasons. Highly significant QTL effects were found for all traits at several sites in the genome. A major portion of the QTL was found on chromosome 2. The effect of the alleles in locus v on thousand grain weight and kernels per ear explained 70–80% of the genetic variation in the traits. QTL × year interaction was found for grain yield. Several different QTL were found within the two-rowed DH lines compared to those found in the six-rowed DH lines. Epistasis between locus v and several loci for yield and yield components indicates that genes are expressed differently in the two ear types. This may explain the difficulties of selecting high yielding lines from crosses between two-rowed and six-rowed barley.Abbreviations DH doubled haploid - QTL quantitative trait locus/loci - RAPD random amplified polymorphic DNA - RFLP restriction fragment length polymorphism - T. Prentice Tystofte Prentice - V. Gold Vogelsanger Gold