棉花种植密度对LAI-2200植物冠层分析仪测定叶面积指数的影响

LAI-2200植物冠层分析仪是一种能直接、无损侧量植物叶面积指数的商业仪器。本研究于2014年在河北省河间市对3个密度棉田LAI-2200测定的叶面积指数(LAI)与实际LAI进行了对比。结果表明,LAI-2200测定的低(6.5万株/hm²)、中(10.5万株/hm²)、高(15.0万株/hm²)3个密度棉田认I的均方根误差(RMSE)分别为0.86,0.62和0.66,提示增加密度有利于提高LAI-2200测定结果的准确性。此外,3个密度棉田蕾期一盛铃期(出苗后47~102d)LAI-2200测定值与实际叶面积指数线性回归的决定系数(R2)分别为0.91,0.86和0.82,纳什效率系数(EF)分别为0.90,0.80和0.84,提示不同密度的模拟质量都比较高,以低密度的模拟质量最佳。盛铃期(出苗后106d)棉株发生倒伏后人工扶起,棉田的自然冠层结构遭到破坏,中高密度棉田LAI-2200刚定值有小于实际LAI的现象,提示倒伏棉田不宜应用LAI-2200进行冠层分析。     

小麦叶片氮素状况与冠层反射光谱指数的关系

利用不同小麦品种在不同施氮水平下的3年田间试验数据,研究了小麦叶片氮积累量与冠层反射光谱间的定量关系。结果显示,不同试验中拔节后叶片氮积累量均随施氮水平呈上升趋势,同时冠层光谱反射率在不同施氮水平下存在明显差异。对于低、中、高蛋白质含量的品种类型,近红外区域若干相邻波段和可见光波段组成的比值植被指数与单位土地面积上叶片氮素积累量的相关关系均表现较好,因此可用760、810、870、950和1 100 nm反射率的平均值与660 nm组成的比值植被指数对不同蛋白质类型小麦品种的叶片氮素积累量进行定量监测,但回归方程的斜率在不同类型品种之间存在显著差异。本研究确立的小麦叶片氮积累量与冠层反射光谱的定量关系可用于不同的小麦品种、生育时期和施氮水平,为小麦氮素营养的监测诊断与精确施肥等提供理论依据和技术途径。     

小麦叶片氮含量与冠层反射光谱指数的定量关系

本文以3种蛋白质类型的小麦品种在不同施氮水平下的3年田间试验为基础，研究了小麦叶片氮含量与冠层反射光谱的定量关系。结果显示，不同试验中拔节后叶片氮含量均随施氮水平呈上升趋势，同时冠层光谱反射率在不同施氮水平下存在明显差异。对于低、中、高籽粒蛋白质含量的品种，叶片氮含量与冠层反射光谱的归一化植被指数NDVI (1 220, 710)和红边位置均有密切的定量关系，决定系数在0.80左右。对于不同品质类型小麦品种，均可利用统一的回归方程描述其叶片氮含量随反射光谱参数的变化，对于低蛋白类型品种，采用单独的回归系数即可提高叶片氮含量估测的准确性。本研究确立的小麦叶片氮含量与冠层反射光谱的定量关系可用于不同的小麦品种、生育时期和施氮水平，为小麦氮素营养的监测诊断与精确施肥等提供理论依据和技术途径。     

小麦叶片氮积累量与冠层反射光谱指数的定量关系

利用不同小麦品种在不同施氮水平下的3年田间试验数据，研究了小麦叶片氮积累量与冠层反射光谱间的定量关系。结果显示，不同试验中拔节后叶片氮积累量均随施氮水平呈上升趋势，同时冠层光谱反射率在不同施氮水平下存在明显差异。对于低、中、高蛋白质含量的品种类型，近红外区域若干相邻波段和可见光波段组成的比值植被指数与单位土地面积上叶片氮素积累量的相关关系均表现较好，因此可用760、810、870、950和1100nm反射率的平均值与660nm组成的比值植被指数对不同蛋白质类型小麦品种的叶片氮素积累量进行定量监测，但回归方程的斜率在不同类型品种之间存在显著差异。本研究确立的小麦叶片氮积累量与冠层反射光谱的定量关系可用于不同的小麦品种、生育时期和施氮水平，为小麦氮素营养的监测诊断与精确施肥等提供理论依据和技术途径。     

竞争指数在小麦品种选育上的应用

对黑龙江省15个主栽品种在不同密度栽培条件下，研究其竞争效应及其量化指标。研究结果表明，竞争指数不仅能够反映小麦品种(系)的竞争能力，而且也可预测其在栽培群体条件下的增产潜力。通过产量竞争指数与性状竞争指数的相关关系表明，主穗小穗数、株穗数和株粒数的竞争指数与产量竞争指数呈显著或极显著正相关，穗长的竞争指数与产量竞争指数相关微弱。     

小麦收获指数的改良

该文从品种改良的角度，对小麦品种收获指数的有关研究结果进行了概述，分析了小麦收获指数改良的生理基础，以期从中获得有益的启示。     

两种植物冠层分析仪测量夏玉米LAI结果比较分析

植物冠层分析仪测量作物叶面积指数存在高估或低估现象,不同仪器的测量结果均与真实值存在差异,这种差异除了与仪器有关,还在不同的作物物候期表现出不同规律。本研究使用LAI-2000、Sunscan两种主流植物冠层分析仪测量夏玉米不同生育期LAI,并与LI-3000C叶面积仪实测结果比较。研究发现：当玉米LAI<1时,LAI-2000测量结果高于实际值,Sunscan测量结果与实际值无显著差异;12时,两种冠层分析仪测量结果均低于实际叶面积指数;不同LAI范围内,LAI-2000、Sunscan测量值与实际值的相关系数不同,最高可达0.9778和0.9637,通过建立测量值和实际值的经验关系模型,对仪器测量值进行校正可减少误差。     

棉花形态发生和叶面积指数的模拟模型

棉花形态发生的模拟以每日生理热效应为主要驱动因子,同时考虑了地膜覆盖后地温升高对气积温的补偿作用。叶面积指数的模拟基于棉花LAI动态消长与物质流的库源关系,量化了棉花生育过程中源或库不足时的LAI增长过程。通过对模型参数的校正和核实,使模型适应于不同类型品种的形态发生和LAI动态模拟。结果表明,叶片数、株高、果枝和果节的模拟精度均差方根(RMSE)分别达到了0.7片、1.6cm、0.8个和3.3个;叶面积指数在不同品种和管理方式下的模拟精度RMSE达到了0.3,表现出较好的吻合度和适用性。     

2种植物冠层分析仪测量夏玉米LAI结果比较分析

为分析两种常用植物冠层分析仪测量玉米叶面积指数的误差规律,为减少玉米叶面积指数测量误差提供依据。使用LAI-2000、Sunscan两种主流植物冠层分析仪测量夏玉米不同生育期LAI,并将测量值与LI-3000C叶面积仪实测值比较。研究发现:当玉米LAI1时,LAI-2000测量结果高于实际值,Sunscan测量结果与实际值无显著差异;1LAI2时,LAI-2000测量结果与实际值无差异,Sunscan测量值低于真实值;玉米LAI2时,两种冠层分析仪测量结果均低于实际叶面积指数;不同LAI范围内,LAI-2000、Sunscan测量值与实际值的相关系数不同,最高可达0.9778和0.9637。不同植物冠层分析仪在玉米不同LAI条件下有不同的测量误差规律;使用经验模型校正仪器测量值,应分不同范围的玉米LAI值进行。     

基于归一化法的双季稻叶面积指数动态预测模型

研究旨在阐明双季稻叶面积指数与辐热积的关系及施氮量对其的影响。选择11个早晚稻品种进行4个施氮水平的小区试验,于关键生育期取样测定叶面积指数(LAI),并对LAI及全生育期的累积辐热积(TEP)进行归一化处理,采用Curve Expert分析软件对相对LAI(RLAI)与相对TEP(RTEP)进行模拟分析,获得6个拟合效果较佳的模拟模型,其中有理方程能够较准确地描述双季稻叶面积指数的动态变化模式,相关系数为0.9677**,具有明确的生物学意义。利用独立的田间试验资料,对构建的模型进行了初步检验。结果表明:早晚稻不同相对TEP所对应的LAI观测值与模拟值之间的根均方差(RMSE)为0.50 m2/m2,表明基于RTEP的RLAI动态模型能够准确地反映双季稻LAI的动态变化。早晚稻群体最大LAI(LAImax)随施氮量的增加呈二次多项式函数增大趋势,相对LAI变化速率随相对辐热积的增加呈"N"形变化趋势。研究结果为早晚稻高产栽培和叶面积指数的精确调控提供了理论支撑。     

Normalization method for canopy temperature as an indirect indicator of yield potential in wheat breeding programs

Canopy temperature (CT) is often related to potential yield and is a possible yield indicator in breeding programs. However, it is difficult to evaluate genetic variations of CT accurately in large-scale investigations, such as breeding programs, because CT is strongly affected by environmental conditions. In this study, to precisely evaluate these genetic variations, we determined the environmental factors that affect CT measurement and proposed a convenient normalization method to minimize their influence. We measured the CT of CT-high or CT-low cultivars in the field under various conditions. We found that as the sun and shade levels were alternated, the CT changed within seconds; the position in the field also critically affected the CT. However, even under these conditions, the differences between cultivars became clearer if CT was normalized by neighboring lines. Additionally, we revealed that CT measurements between 12:00 and 15:00 maximized the difference between cultivars. Using our normalization technique under the favorable conditions specified can help breeders select high-yield lines using CT in breeding programs.     

Run-time calibration of simulation models by integrating remote sensing estimates of leaf area index and canopy nitrogen

Dynamic simulations models may enable for farmers the evaluation of crop and soil management strategies, or may trigger crop and soil management strategies if they are used as warning systems, e.g. for drought risks and for nutrients shortage. Predictions by simulation models may differ from field observations for a variety of reasons, and such deviations can be revealed instantly by traditional or by new field monitoring techniques. The objective of this study was to improve simulation results by integrating remote sensing observations during the growing season in the simulation (i.e. run-time calibration). The Rotask 1.0 simulation model was used as it simulates daily interactions between climate (radiation temperature, vapour pressure, wind speed, precipitation), soils (water holding capacities, soil organic matter dynamics, evaporation) and crops (light interception, dry matter production, nitrogen uptake, transpiration). Various run-time calibration scenarios for replacing simulated values by remotely observed values were tested. For a number of times in the growing season, simulated values of leaf area index (LAI) and canopy nitrogen contents were replaced with values estimated from remote sensing. Field experiments were carried out in the Netherlands in 1997 (validation) and 1998 (calibration) with potato variety Bintje. Destructive field samplings were performed to follow LAI and canopy nitrogen development in the growing season. Remote sensing observations at canopy level were taken by CropScan™ equipment, covering the electromagnetic spectrum between 460–810 nm in eight spectral bands. LAI and canopy nitrogen were monitored at various moments throughout the growing season by relating them with vegetation indices (VI) that were calculated from the combination of specific remote sensing bands. The results of this study show that run-time calibration of mechanistic simulation models may enhance simulation accuracy, depending on the method how additional information is integrated. It is advised to synchronize dry matter balances and internal nitrogen balances in accordance with adjustments to observed calibration variables (in this case LAI and canopy nitrogen content). It is shown an integrated approach follows the actual crop–soil system more closely, which is helpful for specific crop management and precision agriculture in general. Run-time calibration with variables that can be estimated from remote sensing observations gives more accurate simulation results of variables that can not be observed directly, e.g. the evolution of soil inorganic nitrogen contents. High frequencies of remote sensing observations and interpolation in between them, allow reconstructing the evolution of LAI and canopy nitrogen contents to be integrated in the simulation, thereby increasing simulation accuracy of other model variables.     

基于GF-1/2卫星数据的冬小麦叶面积指数反演

叶面积指数(leafareaindex,LAI)是监测作物生长状况的重要参数,准确、快速、大面积估算LAI不仅有助于更好地监测农作物,而且也有助于其在建模、总体作物管理及精准农业中的应用。本研究为了利用国产遥感影像快速、大面积反演冬小麦LAI,以GF-1/2影像作为数据源,提取常用植被指数,结合不同生育期(起身期、拔节期、开花期)实测LAI数据,建立反演冬小麦LAI的单变量和多变量经验模型,并对其进行验证。结果表明, GF-1起身期、GF-1拔节期以及GF-1开花期提取的植被指数中,MSR(modifiedsimpleratio)、GNDVI(greennormalizeddifference vegetationindex)、EVI(enhancedvegetationindex)与LAI间的相关系数最大,分别为0.708、0.671和0.743,说明这些植被指数与冬小麦LAI间的相关性较显著;GF-1不同生育期的反演模型相比,基于拔节期GNDVIGF-1建立的二次多项式模型和基于开花期EVI_GF-1、GSR_GF-1 (green simp...     

Estimating canopy leaf nitrogen concentration in winter wheat based on multi-angular hyperspectral remote sensing

Real-time, nondestructive estimation of crop nitrogen (N) status is highly important for precision N management in winter wheat production. Developing a new N indicator based on the direct link between spectral index and chlorophyll content is important for crop N diagnosis. In this study, we investigated the quantitative relationships between leaf N concentration (LNC) and ground-based multi-angular remote sensing hyperspectral reflectance in winter wheat (Triticum aestivum L.). Field experiments were conducted from 2011 to 2014 across different sites, cultivars, growth stages, N rates, and planting densities, and a novel Multi-angular vegetation index (MAVI_SR) was developed to improve the prediction accuracy and stability of LNC measurement. The optimum vegetation indices (VIs) obtained from 40 traditional indices reported in the literature, as well as normalized difference spectral indices (ND) and Simple Ratio Indices (SR), were tested for their stability in estimating LNC at 13 viewing zenith angles (VZAs). Overall, the coefficient of determination (r²) of spectral reflectance and traditional VIs with LNC decreased with increasing VZA in both the forward and backward scattering directions and reached maximum values at a viewing angle of −20°. Ratio index (RI-1 dB) exhibited the best linear relationship to LNC (r² of 0.837) at the −20° viewing angle, but Enhanced vegetation index (EVI-1) showed the highest r² (0.819) with LNC at the nadir direction. The relationships between the LNC and two-band combinations indicate that there are three sensitive regions with high r², which vary with VZA, usually comprising combinations of blue–red wavelengths, green–red edge wavelengths, and between-red edge wavelengths. To further analyze the relationship between the combination of the three sensitive regions and the sensitive VZAs with LNC, the MAVI_SR index in the form of MAVI_SR = (R538/R768)₋₂₀ − (R478/R634)₊₁₀ was calculated and found to be highly correlated with LNC (r² = 0.897). When independent data were fit to the derived equations, the average relative error (RE) values were 15.5%, 14.3%, and 12.6% between measured and estimated LNC using EVI-1_0°, RI-1 dB_−20°, and MAVI_SR, respectively. These results suggest that the models can accurately estimate LNC in wheat, and the novel MAVI_SR is more effective for estimating LNC than previously reported VIs, independent of years, sites, and growth periods. The results also indicate the importance of taking into account angle effects when analyzing VIs.     

Crop nitrogen demand and canopy area expansion in winter wheat during vegetative growth

The effect of nitrogen (N) on crop growth and productivity is mediated through effects on both light interception (green crop area) and radiation use efficiency (RUE). The effects of N nutrition on these factors were studied using data on green area index (GAI), above-ground dry matter and N uptake from growth analysis measurements in winter wheat from a number of experiments in Denmark with different application rates of N. Only measurements taken prior to anthesis were used in the statistical analyses. The N uptake was found to be proportional to GAI, and to have an additional curvilinear response to dry matter implying decreasing N concentration with increasing dry matter. This supports the hypothesis that nitrogen is associated with both the green surfaces of the crop canopy and with the dry matter component. A model of GAI expansion is presented incorporating three limiting factors: an exponential increase in GAI in thermal time, a minimum leaf area ratio, and a minimum ratio of GAI to N content in above-ground dry matter. This simple function has potential to be used as a tool for targeting timing and rates of N fertilisation in relation to a desired development of GAI. Such N application strategies should also consider the nitrogen nutrition index (NNI), which was defined based on the relationship between N uptake and both GAI and dry matter. The response of RUE to NNI showed a curvilinear response with a tendency for saturation at high NNI. The design of N application strategies should therefore ensure that low NNI is avoided during the most productive periods in the growing season.     

Comparison of osmotic adjustment,leaf proline concentration,canopy temperature and root depth for yield of juncea canola under terminal drought

Two glasshouse and two field experiments were conducted in 2013 and 2014 to compare the relative importance of four physiological traits: osmotic adjustment (OA), leaf proline concentration, canopy temperature depression (CTD) and root depth on drought performance of canola quality B. juncea (juncea canola). Glasshouse experiments were conducted at The University of Melbourne, Parkville, and field experiments were conducted at Horsham, Victoria. The experiments used juncea canola hybrids and their parental lines and were laid out in a randomised complete block design with three replications. The glasshouse experiments consisted of two treatments, well watered and water deficit from first open flower to maturity, whereas the field experiments were sown at a site that received 266 mm annual rainfall in 2014. In the glasshouse, canopy temperature depression was the only trait to show a positive and consistent association with drought performance of juncea canola. Cooler canopy temperature was also associated with improved yield in field experiments. Root depth was positively correlated with CTD in 2014 in glasshouse, whereas no correlation of root depth with OA and leaf proline was observed. The results indicated that CTD was the only reliable trait among those tested to screen juncea canola for drought tolerance. Root depth of juncea canola hybrids was a constitutive trait and probably was a result of hybrid vigour.     

Monosomic analysis of Helminthosporium leaf blight resistance genes in wheat

A set of 21 monosomic (2n ‐ 1) and the disomic (2n) lines of the ‘Chinese Spring’ cultivar were crossed with ‘Chirya‐3′, the CIMMYT synthetic wheat line which has been identified as highly resistant for Helminthosporium leaf blight disease (HLB), in order to locate the genes governing disease resistance. The F₁ and segregating populations were challenged and screened against the most virulent pure mono‐conidial HLB isolate KL‐8 (Karnal, India). The F₁ progenies of the crosses were found to be susceptible because of the recessive nature of resistance. The F₂ progeny of the control cross (‘Chinese Spring’בChirya‐3’), segregated in the ratio of 1: 15 (resistant: susceptible), indicating that resistance to HLB was controlled by a pair of recessive genes. While the F₂ progeny of 19 monosomic crosses segregated in the ratio of 1: 15 (resistant: susceptible), the progeny of the remaining two crosses, 7B and 7D, deviated significantly from the ratio, revealing that 7B and 7D were the critical chromosomes for resistance genes that were located one on each chromosome. Moreover, the critical lines, 7B and 7D, confirmed the digenic complementary recessive nature of gene action by fitting well with the overall pooled F₂ segregation ratio of 13: 51 (resistant: susceptible) as expected for digenic complementary recessive resistance. The F₃ segregation ratios of the critical crosses, based on their pooled F₂ analysis, was estimated as 19: 32: 13 (non‐segregating susceptible: segregating as susceptible and resistant: non‐segregating resistant). F₃ progenies when tested with these ratios showed goodness‐of‐fit, confirming that the two pairs of recessive resistance genes were located on chromosomes 7B and 7D.     

Phenological development, leaf emergence, tillering and leaf area index, and duration of spring wheat across Europe in response to CO2 and ozone

Phenological development, leaf emergence, tillering and leaf area index (LAI), and duration (LAD) of spring wheat cv. Minaret, grown in open-top chambers at different sites throughout Europe for up to 3 years at each site, were investigated in response to elevated CO₂ (ambient CO₂×2) and ozone (ambient ozone ×1.5) concentrations.

Phenological development varied among experiments and was partly explained by differences in temperature among sites and years. There was a weak positive relationship between the thermal rate of development and the mean daylength for the period from emergence to anthesis. Main stems produced on average 7.7 leaves with little variation among experiments. Variation was higher for the thermal rate of leaf emergence, which was partly explained by differences in the rate of change of daylength at plant emergence among seasons. Phenological development, rate of leaf emergence and final leaf number were not affected by CO₂ and ozone exposure. Responses of tillering and LAI to CO₂ and ozone exposure were significant only in some experiments. However, the direction of responses was consistent for most experiments. The number of tillers and ears per plant, respectively, was increased as a result of CO₂ enrichment by about 13% at the beginning of stem elongation (DC31), at anthesis and at maturity. Exposure to ozone had no effect on tillering. LAI was increased as a result of CO₂ elevation by about 11% at DC31 and by about 14% at anthesis. Ozone exposure reduced LAI at anthesis by about 9%. No such effect was observed at DC31. There were very few interactive effects of CO₂ and ozone on tillering and LAI. Variations in tillering and LAI, and their responses to CO₂ and ozone exposure, were partly explained by single linear relationships considering differences in plant density, tiller density and the duration of developmental phases among experiments. Consideration of temperature and incident photosynthetically active radiation in this analysis did not reduce the unexplained variation. There was a negative effect of ozone exposure on leaf area duration at most sites. Direct effects of elevated CO₂ concentration on leaf senescence, both positive and negative, were observed in some experiments. There was evidence in several experiments that elevated CO₂ concentration ameliorated the negative effect of ozone on leaf area duration. It was concluded from these results that an analysis of the interactive effects of climate, CO₂ and ozone on canopy development requires reference to the physiological processes involved.     

Genotypic differences in flag leaf area and their contribution to grain yield in wheat

Summary Flag leaf areas of the wheat variety Chinese Spring, six chromosome substitution lines of the variety Hope into Chinese Spring and their hybrids were measured by the planimeter method. Data on tiller number at ear emergence and ear number and grain yield at harvest were also obtained. Considerable variation existed in each of the characters investigated. The inheritance of flag leaf area showed some evidence of over dominance and non-allelic interaction while ear number was mainly under additive genetic control with partial dominance. Highly significant associations were found between flag leaf area, ear number and grain yield per plant. The importance of flag leaf area in yield determination was discussed in the light of the results obtained. It was concluded that despite the correlation between flag leaf area and grain yield, the major components of yield and grain yield itself, still offer the best guide for selection.     

Combining ability analysis for harvest index in winter wheat

Summary Cereal breeders have used harvest index (HI) as a selection criterion in segregating generations to identify physiologically superior lines with improved partitioning of total assimilate into grain. Information on combining ability for HI of the hard red winter wheat (Triticum aestivum L.) cultivars of the Southern Great Plains is not available. A study was undertaken to examine HI of seven genetically diverse winter wheat parents, evaluate their general combining ability (GCA) and specific combining ability (SCA) effects, and study correlations of HI with several agronomic traits. The seven parents were crossed in a half-diallel mating design to produce 21 crosses. The F₁'s, their F₂ progenies, and the parents were evaluated in replicated field tests at Stillwater and at Lahoma, OK. The combining ability analysis was performed using Griffing's Method 4, Model 1. The results showed significant variation among parents for HI. The GCA and the SCA effects were mostly inconsistent between generations and between environments. However, parents with consistently high HI and positive GCA estimates were identified. The progeny with high HI mostly resulted from parents with high GCA estimates. The correlations between HI and agronomic traits indicated that improvement in HI should also result in high grain yield, early maturity, and short plant height.