Remote Assessment of Wheat Canopies under Various Cultivation Conditions Using Polarized Reflectance

Abstract

The polarization of light reflected from crop canopies gives information on the canopy structure, such as the distribution of leaf inclinations. In order to verify those findings and to put the technique to practical use, we conducted two experiments in wheat fields. In the first experiment, the reflectance and polarized reflectance at 660 nm in the canopies of wheat plants, sown in both narrow and wide rows, and at two levels of topdressing, were measured periodically with a spectropolarimeter. We also probed the leaf orientation geometry of the plants using a 3-D digitizer and a plant canopy analyzer (LAI-2000). In the second experiment, we observed the polarization of light reflected from wheat planted in plots fertilized with basal dressing, and topdressing at the jointing and booting stages. Polarization showed a seasonal change with an upward convex clearly indicating the heading time. This pattern was not found by conventional band reflectance. Using polarization, it was possible to detect the differences in row width and fertilization conditions during the booting stage. The mean leaf inclination angle (MLI) detected with the 3-D digitizer and the mean tip angle (MTA) detected with the LAI-2000 were relatively closely correlated with the polarization than the reflectance at 660 nm and normalized difference vegetation index (NDVI) that was derived from the reflectance at 660 nm and 830 nm. Topdressing at the jointing stage was well detected by polarization obtained at the heading stage. Polarization measurements are useful in practical terms for remote detection of changes in stand geometry induced by cultivation management such as topdressing.     

Estimating Rice Leaf Greenness (SPAD) Using Fixed-Point Continuous Observations of Visible Red and Near Infrared Narrow-Band Digital Images

Abstract

A narrow-band dual camera system demonstrated a new close-range sensing technique to seasonally track trends in leaf greenness in rice paddies. A weatherproof digital imaging system for the visible red (RED, 620?650 nm) and near infrared band (NIR, 820?900 nm) was positioned 12 m above a 600-m² rice field. During the 2009 and 2010 paddyrice seasons, the system automatically logged images at 10-min intervals throughout the day. Radiometric corrections for the images utilized solar irradiance sensors and prior calibration to calculate 0900-1500 JST daily-averaged reflectance factors (DARF). The DARF in RED (DARF-RED) and NIR (DARF-NIR) values were transformed to provide a daily-averaged normalizeddifference vegetation index (DA-NDVI). The DA-NDVI increased more rapidly in the vegetative growth period, and reached an asymptotic plateau earlier than the DARF-NIR. From transplanting to harvest, leaf greenness values (measured by the SPAD index) were measured for the central part of the uppermost leaves of targeted canopies weekly with a chlorophyll meter. We developed a leaf greenness index (LGI), the ratio of DA-NDVI to DARF-NIR, and a simple calculation method for area means to reduce the background effect. The modified area means of LGI followed the seasonal trend in SPAD value well; its patternwas inherently different from the patterns of any of the original three parameters: DARF-RED, DARF-NIR or DA-NDVI. Throughout the paddy seasons in the two years, a regression equation for estimating SPAD values using the LGI, daily solar radiation, the cosine of angle between the view and the meridian directions and the cosine of culmination solar zenith angle performed favorably (R²=0.815). The nitrogen concentration per dry plant hill (g kg-¹) had a close relation to the SPAD values estimated using the equation.     

Testing Polarization Measurements with Adjusted View Zenith Angles in Varying Illumination Conditions for Detecting Leaf Orientation of Wheat Canopy

Abstract:

The previous work revealed that the polarization of light reflected from heading wheat canopies allowed the detection of changes in the canopy structure, i.e., the leaf inclination angle. Accordingly, in order to improve measurement accuracy in this study we examined the effects of the solar zenith angle (= 90º–solar elevation) and weather conditions at the time of polarization measurements for the light reflected from wheat canopies that were fertilized by different means. We measured polarization in the 660 nm spectral band from the heading canopies of wheat, which were grown in plots fertilized with a basal dressing and then top-dressed at the jointing and booting stages. The radiometric measurements were carried out at various solar zenith angles: 22º–41º on two proximal days, one overcast and the other clear. An empirical method for the adjustment of view zenith angle, based on the solar position at the time of measurement, was effective for the measurement of the degree of polarization (i.e., ratio of the polarized part of reflected light to the total reflected light energy) to eliminate interference due to the change in solar zenith angle. Although the mean values of polarization degree measured in overcast conditions were significantly lower than those measured under clear conditions, the plots top-dressed at the jointing stage could be detected via the polarized reflected light measured under both conditions of illumination.     

小麦玉米一体化群体配置对小麦冠层结构和产量影响

为探索冬小麦-夏玉米一体化种植中小麦的适宜群体配置模式,设置20 cm-20 cm（R₁）、12 cm-12 cm-12 cm-24 cm（R₂）及13 cm-20 cm（R₃）三种行距处理方式和120 kg·hm^-2（S₁）、157.5 kg·hm^-2（S₂）及195 kg·hm^-2（S₃）三种播量,研究了行距和播量对小麦冠层结构特征和光合特性及产量的影响。结果表明,不同处理对各指标的影响因小麦生育时期的变化而不同。在孕穗至开花期, R₁S₁处理的小麦叶片SPAD值、净光合速率（P_n）及气孔导度（G_s）高于其他处理,开花期后R₂S₂处理表现出明显的光合优势。其中,R₂S₂处理的小麦LAI、叶倾角（MTA）在开花期后高于其他处理,在花后10 d之后其SPAD、P_n值最高。在不同处理中,R₂S₂处理产量最高,这主要归因于其有较高的穗数和千粒重。因此,在本试验条件下小麦高产的最佳群体配置是行距12 cm-12 cm-12 cm-24 cm和播量157.5 kg·hm^-2。     

冬前镇压和灌溉对冬小麦灌浆期旗叶光合特性和叶绿体超微结构的影响

为明确冬前镇压和灌溉对冬小麦灌浆期旗叶功能的影响,以济麦22为材料,在2016-2017小麦生长季,对其进行冬前镇压+灌溉(C+I)、灌溉(I)和镇压(C)处理,以常规种植管理为对照(CK),研究不同冬前栽培措施对冬小麦灌浆期土壤微环境、旗叶光合特性和叶绿体超微结构以及最终产量和生物量的影响。结果表明,与CK相比,C、I及C+I处理都可提高麦田土壤含水量和土壤温度,可增加花后14～28d旗叶叶绿素相对含量(SPAD)、灌浆期旗叶最大光学效率(Fv/Fm)、净光合速率(Pn)和蒸腾速率(Tr),缓解旗叶SPAD、Fv/Fm、Pn和Tr在灌浆后期的下降,其中以C+I处理的效果最佳;灌浆中后期(花后21d),CK条件下小麦植株旗叶部分叶绿体呈圆形,大部分基粒片层变形且排列紊乱,可见较多的亲锇颗粒,但C+I、C和I处理下叶绿体的破坏程度降低,较多的叶绿体呈椭圆形,单位面积内叶绿体数和叶绿体基粒数提高,基粒片层较CK清晰且排列紧密,亲锇颗粒数量减少,其中C+I和I处理对叶绿体超微结构的改善作用大于C处理。这说明在本试验条件下,冬前镇压+灌溉较单独灌溉或镇压更有利于改善小麦灌浆期旗叶光合功能,缓解灌浆后期旗叶的衰老,促进小麦产量形成。     

春季不同时期低温对小麦光合特性和粒重形成的影响

为探讨春季低温导致小麦粒重下降的生理机制,以春性品种扬麦16和半冬性品种徐麦30为材料,分别于倒二叶出生期、孕穗期和开花期对小麦进行人工气候室低温处理,研究不同时期低温对小麦光合生理特性、干物质积累和转运及强、弱势粒粒重形成的影响。结果表明,不同时期低温对叶片SPAD值的影响均表现为低温处理开始至结束后3 d持续下降,结束后6～9 d逐渐回升,两品种在低温处理结束当天和处理后3 d均以孕穗期低温处理下SPAD值降幅最大。不同时期低温处理显著降低叶片净光合速率和气孔导度,并影响花前干物质转运和花后干物质积累。与孕穗期、开花期低温处理相比,倒二叶出生期低温处理显著降低小麦花前干物质转运量,但提高花后干物质积累及其对籽粒产量的贡献率,千粒重降幅最小,扬麦16和徐麦30分别仅为4.49%和4.20%。不同时期低温处理下小麦强势粒粒重的降幅均小于弱势粒,倒二叶出生期低温处理下弱势粒粒重降幅显著低于孕穗期和开花期低温处理。相关性分析表明,低温胁迫下小麦平均千粒重和强势粒粒重相关性不显著(r=0.319,P>0.05),但与弱势粒粒重显著相关(r=0.691,P<0.05)。综上,春季低温胁迫主要通过影响小麦开花前后的光合作用和同化物向籽粒的转运,限制弱势粒的灌浆充实,最终导致粒重下降。     

基于三波段光谱指数的春小麦叶片水分含量估算

为探讨利用三波段植被指数（three-band index, 3BI）对春小麦叶片水分含量（leaf water content, LWC）估算的可行性,在田间尺度上,利用ASD-FieldSpec-3光谱仪测定春小麦抽穗期冠层光谱反射率,采用任意波段组合方法,分别建立两波段植被指数（two-band index, 2BI）包括比值植被指数（RVI）、归一化植被指数（NDVI）、差值植被指数（DVI）及3BI,并对单波段反射率、两波段植被指数和三波段植被指数与春小麦抽穗期LWC之间进行相关性分析,筛选稳定的光谱参数,基于人工神经网络（artificial neural network, ANN）、K近邻（K-nearest neighbors, KNN）和支持向量回归（support vector regression, SVR）等3种机器学习算法,建立有效波段组合运算的抽穗期春小麦LWC估算模型,并利用独立样本对模型精度进行检验和评价。结果表明,单波段反射率、2BI和3BI与春小麦抽穗期LWC之间的相关性均达极显著水平（P＜0.01）,而相关系数差异较大,绝对值分别为0.23、0.62、0.94,说明组合波段展现了光谱隐含信息,避免有效光谱信息的丢失;估算模型中,春小麦抽穗期以KNN算法和最佳3BI组合变量（3BI-5_{(1075, 1095, 1085)}、3BI-6_{(1100, 400, 1097)}）构建的模型拟合度最高（r²=0.83）,均方根误差最小（RMSE=2.14%）,相对偏差百分比超出了2.0以上（RPD=2.31）,说明该模型具有一定的预测能力。由此可见,通过任意波段组合,可明显提高3BI与春小麦LWC的关联度,且基于K近邻算法构建的模型具有较好的稳定性和估算能力。     

Improvement of nitrogen management in rice paddy fields using chlorophyll meter (SPAD)

Optimum rate and timing application of nitrogen (N) fertilizer are most crucial in achieving high yield in irrigated lowland rice. In order to assess leaf N status, a semidwarf rice cultivar (Khazar) was grown with different N application treatments (0, 40, 80, and 120 kg N ha⁻¹ splited at transplanting, midtillering, and panicle initiation stages) in a sandy soil in Guilan Province, Iran, in 2003. The chlorophyll meter (SPAD 502) readings were recorded and leaf N concentrations were measured on the uppermost fully expanded leaf in rice plants at 10-day internals from 19 days after transplanting to grain maturity. Regression analysis showed that the SPAD readings predicted only 23% of changes in the leaf N concentration based on pooled data of leaf dry weight (N _dw) for all growth stages. However, adjusting the SPAD readings for specific leaf weight (SPAD/SLW) improved the estimation of N _dw, up to 88%. Specific leaf weight (SLW), SPAD readings, leaf area and weight as independent variables in a multiple regression analysis predicted 96% of the N _dw changes, while SPAD readings independently predicted about 80% of leaf N concentration changes on the basis of leaf area (N _a). It seems that chlorophyll meter provides a simple, rapid, and nondestructive method to estimate the leaf N concentration based on leaf area, and could be reliably exploited to predict the exact N fertilizer topdressing in rice.     

冬小麦返青期主要生长指标的HJ-1A/1B遥感影像监测

为进一步深化作物长势遥感监测机理与方法,给大田管理及时提供信息与技术,结合2011-2013年定点观测试验,以HJ-1A/1B数据为遥感影像源,研究了返青期冬小麦主要生长指标、籽粒品质参数和产量间及其与遥感变量间的定量关系,分别构建及评价基于HJ-1A/1B影像遥感变量的返青期叶面积指数、生物量、SPAD值和叶片含氮量监测模型。结果表明,返青期,归一化植被指数（NDVI）、比值植被指数（RVI）、蓝光波段反射率（B₁）和RVI可分别作为监测冬小麦叶面积指数、生物量、SPAD和叶片含氮量的敏感遥感变量,所构建的遥感监测模型可靠且精度较高,模型的决定系数（R²）分别为0.62、0.56、0.46和0.58,均方根误差（RMSE）分别为0.42、452.3 kg·hm^-2、4.39和0.54%。同时,对冬小麦不同等级主要生长指标进行遥感监测并制图,量化表达了主要生长指标区域空间分布。     

冬小麦叶面积指数的品种差异性与高光谱估算研究

为给小麦叶面积指数（LAI）的高光谱估算提供技术支持,基于2年大田试验,以4个河南主推品种为材料,对小麦LAI和冠层光谱变化特点、估算模型及其品种间的差异等进行了系统分析。结果表明,在生育期内不同冬小麦品种冠层光谱反射率的变化与LAI变化有差异;在相同LAI下,不同冬小麦品种的光谱曲线存在差异。利用400~900 nm范围内冠层光谱反射率的任意两波段组合的比值光谱指数（RSI）、归一化差值光谱指数（NDSI）和差值光谱指数（DSI）所建立的单品种模型以及不同品种综合模型的决定系数（r）均达到0.84以上,单品种模型的r和调整r分别较综合模型高出3.1%~4.8%和2.0%~4.2%。利用独立于建模样本以外的数据对上述模型进行检验,单品种模型预测的r较综合模型提高了0.6%~11.0%,而均方根误差降低了10.0%~37.0%。因此,在利用高光谱遥感技术估算冬小麦LAI时,可以通过建立单品种模型来提高估算精度。     

多遥感光谱指标结合进行大田冬小麦叶片叶绿素含量估测研究

为解决大田冬小麦叶片叶绿素含量估测模型精度低、通用性弱的问题,在获取冬小麦拔节期和抽穗期冠层红光波段反射率(BR_red)和近红外波段反射率(BR_nir)的基础上,计算归一化差值植被指数(NDVI)、差值植被指数(DVI)、比值植被指数(RVI)、土壤调节植被指数(SAVI)、改进型比值植被指数(MSR)、重归一化植被指数(RDVI)、II型增强植被指数(EVI2)和非线性植被指数(NLI)等8个植被指数。经统计分析,选择与叶片叶绿素含量(SPAD值)相关性较好的5个遥感光谱指标(NDVI、MSR、NLI、BR_red和RVI)作为输入变量,建立了冬小麦叶片叶绿素含量的BP神经网络估测模型(WWLCC_BP),并对估测模型进行精度验证。结果表明,WWLCC_BP估测模型在拔节期估测的决定系数(r²)为0.84,均方根误差(RMSE)为5.39,平均相对误差(ARE)为9.87%。抽穗期的估测效果与拔节期较为一致。将WWLCC_BP和高分六号影像...     

Evaluation of the SPAD Value in Faba Bean (Vicia fabaL.) Leaves in Relation to Different Fertilizer Applications

Abstract

The correlations of the reading of a portable chlorophyll meter (SPAD-502) with the chlorophyll and N contents of leaves of two faba bean (Vicia fabaL.) cultivars, Japanese (Ryousai-issun) and Egyptian (Cairo 241), were examined. The SPAD readings positively correlated (ρ<0.01) with the chlorophyll contents and the r² values were 0.99 and 1.00 for Ryousai-issun and Cairo 241, respectively. A close linear relationship (ρ0.001) was observed between SPAD reading and total leaf N content at the pod development stage of faba bean plants with r² = 0.88 and 0.99 for Ryousai-issun and Cairo 241, respectively. The SPAD reading was the highest in the 2^nd to 4^th leaves counted from the top (the youngest fully expanded leaves). The changes in leaf chlorophyll content of both cultivars from 3 weeks after transplanting to the ripening stage showed an incomplete “M” type curve. SPAD readings were significant¬ly higher in Ryousai-issun than in Cairo 241 throughout the growth season. Organic fertilizers application improved faba bean plant growth. These results suggest that the SPAD-502 chlorophyll meter can be used to measure chlorophyll and nitrogen contents of faba bean leaves for quick screening faba bean genotypes.     

基于无人机多光谱遥感的冬小麦叶片含水量反演

为了快速监测小麦叶片水分含量,以敏感波段组和植被指数组2种变量分别作为输入变量,以地面同步观测的冬小麦叶片含水量作为输出变量,分别采用偏最小二乘(partial least squares, PLS)、极限学习机(extreme learning machine, ELM)和粒子群算法(particle swarm optimization, PSO)优化极限学习机,建立冬小麦叶片含水量预测模型,并对其反演效果进行比较。结果表明,光谱反射率和植被指数与叶片含水量之间存在较为密切的相关性,依此确定的敏感光谱波段为红光、蓝光和近红外波段,敏感植被指数为绿度指数、过红指数、归一化绿红差值指数、三角形植被指数和过绿指数。从2种变量的建模效果看,基于植被指数组构建的模型的精度和稳定性均优于敏感波段组,其中基于植被指数组的PSO-ELM模型在6个叶片水分含量反演模型中表现最佳,其r²和RMSE分别为0.98和0.26%。利用最优模型反演得到研究区冬小麦叶片含水量的分布范围为45%～75%,平均为64.57%,反演结果与地面实测较相符,说明基于无人机光谱数据通过建立以植被指数为...     

越冬前冬小麦主茎叶片几何参数模型研究

为了定量分析冬小麦越冬前叶片主要几何参数与器官生物量及比叶重的关系,以小麦品种济麦22、泰农18和鲁原502为材料,于2013-2014和2014-2015年冬小麦生长季内开展了品种和施氮试验,通过分析越冬前叶长和叶宽与器官生物量和比叶重之间的定量关系,以及叶弦角和叶切角与比叶重之间的关系,构建了冬小麦越冬前叶片几何参数模型。经独立试验资料检验,冬小麦越冬前叶片主要几何参数叶长、最大叶宽、叶切角和叶弦角实测值与模拟值的RMSE、平均绝对误差（d_a）、平均相对误差（d_ap）和R分别为1.453 cm (n=46)、1.136 cm、11.997%和0.916;0.093 cm (n=46)、0.073 cm、13.396%和0.837;23.906°(n=46)、16.059°、52.153%和0.556;23.706°(n=46)、19.818°、53.966%和0.787,均达极显著水平（P<0.001）,说明实测值与模拟值的吻合程度较好。所建模型可较好地模拟不同品种、不同施氮水平下冬小麦越冬前叶片主要几何参数。     

区域尺度冬小麦叶绿素含量的高光谱预测和空间变异研究

为从区域尺度探讨小麦SPAD的近地高光谱遥感监测技术,采用ASDField Spec 3.0型便携式高光谱仪获取的冬小麦冠层高光谱数据,利用相关分析和偏最小二乘法(PLSR)对SPAD进行建模预测,并采用地统计学方法进行空间变异制图。结果表明,冬小麦叶片SPAD值在不同生长阶段存在一定的差异,但在不同区域之间差异不显著。基于PLSR建立模型,并利用原始光谱和二阶导数光谱进行预测,R~2分别为0.653和0.995,均方根误差分别为2.622和0.327,相对析误差分别为1.549和13.66。综合来看,二阶导数光谱所建立的模型预测能力比原始光谱好。选择拔节期和成熟期进行区域化表达,与实测得到的SPAD空间分布图相比,采用全光谱数据和二阶导数光谱数据预测的SPAD均表现出了较高的空间相似性,其中二阶导数接近实测值。     

Hyperspectral remote sensing of yellow mosaic severity and associated pigment losses in Vigna mungo using multinomial logistic regression models

Yellow mosaic disease (YMD) has been a serious threat to blackgram cultivation especially during post-monsoon season. Visual assessment of disease severity is qualitative and time consuming. Rapid and non-destructive estimation of YMD by hyperspectral remote sensing has not been attempted so far on any of its hosts. Field studies were conducted for two seasons with eight blackgram genotypes having differential response to YMD. Comparison of mean reflectance spectra of the healthy and YMD infested leaves showed changes in all the broad band regions. However, reflectance sensitivity analysis of the narrow-band hyperspectral data revealed a sharp increase in reflectance from the diseased leaves compare to healthy at 669 (red), 505 and 510 nm (blue). ANOVA showed a significant decrease in leaf chlorophyll (p < 0.0001) with increase in disease severity, while no such relationship was observed for relative water content. By plotting coefficients of determination (R²) between leaf chlorophyll and percent reflectance at one nm wavelength interval, two individual bands (R₅₇₁; R₇₀₅) and two band ratios (R₅₇₁/R₇₂₁; R₇₀₅/R₅₉₃) with highest R² values were selected. These bands showed a significant linear relationship with SPAD chlorophyll readings (R² range 0.781–0.814) and spectrometric estimates of total chlorophyll content (R² range 0.477–0.565). Further, the relationship was stronger for band ratios compared to single bands. With optimal spectral reflectance ratios as inputs, disease prediction models were built using multinomial logistic regression (MLR) technique. Based on model fit statistics, reflectance ratios R₅₇₁/R₇₂₁ and R₇₀₅/R₅₉₃ were found better than the individual bands R₅₇₁ and R₇₀₅. Validation of MLR models using an independent test data set showed that the overall percentage of correct classification of the plant into one of the diseased categories was essentially same for both the ratios (68.75%). However, the MLR model using R₇₀₅/R₅₉₃ as dependent variable was of greater accuracy as it gave lower values of standard errors for slopes (β_G range 9.79–36.73) and highly significant estimates of intercept and slope (p < 0.05). Thus the models developed in this study have potential use for rapid and non-destructive estimation of leaf chlorophyll and yellow mosaic disease severity in blackgram.     

不同土壤质地小麦叶片叶绿素的高光谱响应及估测模型

为给小麦生长过程中叶绿素的实时监测和氮肥调控提供参考,设置3种不同土壤质地(沙土、壤土和粘土)、5种不同施氮水平(0、120、225、330和435kg·hm-2)和3个河南省主栽小麦品种(矮抗58、周麦22和郑麦366),同步测定小麦主要生育时期冠层光谱反射率和叶绿素(Chla+b)含量,系统分析了3种土壤质地条件下小麦Chla+b含量与350~1 050nm波段范围内冠层光谱参数的相关关系。结果表明,3种土壤质地下小麦叶绿素的冠层光谱响应趋势基本一致。光谱指数REPIG和mND705对叶片Chla+b含量的监测效果较好,建模决定系数分别为0.76和0.75。利用独立样本数据对用于建模的此二光谱参数进行检验,其预测效果表现较为稳定,预测决定系数分别为0.87和0.85,均方根偏差分别为0.46和0.48。说明利用光谱指数REPIG和mND705为自变量建立的估测模型可以较好地预测当地生产条件下小麦叶片叶绿素,同时为氮肥施用及调控提供技术依据。     

不同土壤肥力条件下麦秆还田与氮肥运筹对杂交稻氮素利用、产量及米质的影响

以杂交稻F优498为材料,研究了高、低土壤肥力下麦秆覆盖与氮肥运筹对杂交稻主要生育期氮素吸收利用特征、产量及米质的影响,并探讨了不同土壤肥力下麦秆覆盖和氮肥运筹对结实期剑叶SPAD值与稻米品质的形成的影响。结果表明,不同土壤肥力下,麦秆覆盖均有效促进杂交稻各生育时期氮素积累,提高了氮素利用效率以及稻谷产量,增加了稻米蛋白质含量、稻米胶稠度,显著降低了稻米垩白度以及垩白粒率,且高土壤肥力下麦秆覆盖优于低土壤肥力下麦秆覆盖处理。同时,不同土壤肥力下麦秆覆盖处理,均以m基肥∶m蘖肥∶m穗肥为3∶3∶4的氮肥运筹模式最优,均能有效调节水稻灌浆结实期叶片SPAD值,提高水稻氮素吸收利用效率及稻谷产量;但稻米品质方面,高土壤肥力以m基肥∶m蘖肥∶m穗肥为5∶3∶2时最佳;而低土壤肥力可适当提高氮肥后移比例,以m基肥∶m蘖肥∶m穗肥=3∶3∶4最佳。相关分析表明,水稻灌浆期剑叶SPAD值与稻米出糙率、整精米率以及蛋白质含量显著或极显著正相关(r=0.47*~0.90**);与垩百度、垩白粒率负相关,但相关未达显著水平;而高土壤肥力下稻米品质各项指标分别与齐穗后19~27d剑叶SPAD值,低土壤肥力下麦秆覆盖与齐穗后13~19d剑叶SPAD值相关系数最大。     

基于新型植被指数的冬小麦覆盖度遥感估算

为提高冬小麦覆盖度估测精度,从增强近红外与红光差别的数学变换原理出发,构建了一种新型植被指数(NDVIn),再基于2013、2014年冬小麦冠层高光谱和模拟的资源三号卫星宽波段多光谱数据,分别构建基于常规植被指数(NDVI)与NDVIn的冬小麦覆盖度估算模型,然后利用留一交叉验证法对模型精度进行评价。结果表明,当n=6时,新生成的植被指数NDVI6对冬小麦农田覆盖度具有最好的估算性能,利用其基于小麦冠层高光谱及卫星多光谱数据建立的冬小麦覆盖度估算模型的决定系数r2分别为0.84、0.85,RMSE分别为0.092、0.091,模型精度均好于常规指数NDVI的估算结果。说明NDVI6用于估测冬小麦覆盖度具有可行性。     

秋季耕作方式对旱地麦-玉二熟区小麦产量形成的影响

为明确秋季耕作方式对旱地麦-玉二熟体系小麦籽粒产量形成的影响,于2019年6月至2021年6月,在豫西典型旱作麦-玉二熟区的洛阳市孟津区小浪底镇明达村,选择前茬夏玉米免耕的田块,设置秋深松、秋免耕和秋旋耕3种耕作方式,分析了不同秋季耕作方式下两个试验年度的小麦籽粒产量及其构成因素和穗部性状以及2020-2021年度的小麦群体茎蘖数、孕穗后的旗叶净光合速率（P_n）和干物质积累转运特性。结果表明,秋季耕作方式对小麦产量、穗部性状、旗叶P_n和干物质积累转运特性均有显著的调节作用。与秋旋耕相比,秋深松的小麦茎蘖数除返青期外均显著增加,穗数增加5.74%~16.06%;秋深松虽然对小麦旗叶P_n无显著影响,但提高灌浆中后期的旗叶SPAD值,显著改善了干物质积累转运特性,从而使千粒重增加,其中2019-2020年度使穗长和小穗数分别提高7.50%和9.42%,最终使籽粒产量提高9.77%~19.09%。秋免耕后,小麦孕穗和抽穗期的叶片P_n、返青至开花期的干物质积累量、花前干物质转运量及其对籽粒产量的贡献率也较秋旋耕均显著降低,而花后干物质对籽粒产量贡献率提高7.35个百分点,从而保证了籽粒产量无显著下降。与秋免耕相比,秋深松下不同生育时期的茎蘖数均显著增加,孕穗至灌浆中后期的叶片P_n,灌浆中后期的旗叶SPAD值,返青-成熟期的干物质积累量,花前干物质转运量、转运效率及其对籽粒产量的贡献率分别提高7.16%~18.41%、10.27%、12.25%~19.97%、42.19%、4.02个百分点和11.95个百分点,其中2019-2020年度穗长和小穗数分别增加7.50%和8.41%,穗数和籽粒产量分别提高16.74%~17.63%和10.31%~23.63%。综上,秋深松不仅可增加小麦穗数,而且可改善旗叶光合及干物质积累转运特性,进而提高籽粒产量,是旱地麦-玉二熟区实现小麦高产的耕作方式。