基于可见光光谱扫描的春玉米氮素营养诊断

采用可见光光谱扫描研究田间条件下春玉米冠层图像色彩参数和氮素营养指标之间的相关性以及简便、快捷、非接触性的作物氮素营养诊断方法。结果表明,春玉米冠层图像色彩参数与氮素营养指标间的相关性依次为6叶期>9叶期>3叶期。在6叶期,春玉米冠层图像色彩参数B、R/G、G/B、G/L、B/L、G/(R+G+B)均与氮素营养指标存在显著或极显著的线性相关关系,其中,G/(R+G+B)与氮素营养指标间的线性正相关性最高。运用可见光光谱扫描的数字图像进行东北地区春玉米氮素营养诊断是可行的,6叶期可作为春玉米氮素营养诊断的关键时期,G/(R+G+B)是春玉米氮素营养诊断的最佳冠层图像色彩参数。     

基于数字图像分析技术的橡胶树叶片氮含量预测

为建立橡胶树氮素营养快速诊断技术,利用数码相机获取橡胶树叶片图像,运用数字图像处理技术提取叶片图像的颜色特征参数,分析颜色特征参数与橡胶树叶片氮含量的相关性,并建立回归模型。结果表明,9个颜色特征参数R/B、B/(R+G)、R/(G+B)、R/(R+G+B)、B/(R+G+B)、(B+G)/(R+G+B)、(R-B)/(R+G+B)、(R-B)/(B+R)和G/(R-B)与橡胶树叶片氮含量相关性较好,综合评价得出G/(R-B)所建立的橡胶树热研7-33-97叶片氮含量二次多项式估测模型最优,模型校正决定系数为81.04％,预测相对误差和均方根误差分别为10.91％和0.31％,表明利用数字图像分析技术可以进行成龄橡胶树热研7-33-97叶片氮素含量营养诊断。     

数字图像技术在马铃薯氮素营养诊断中的应用

应用数码相机获取马铃薯冠层图像色彩信息,探索出马铃薯氮营养状况的一种新方法。结果表明,在块茎形成期和块茎膨大期,数码相机获取的数字图像分析得到的冠层绿光与蓝光比值(G/B)与其它描述马铃薯氮素营养状况的指标如土壤无机氮、植株全氮含量、叶柄硝酸盐浓度、叶绿素仪读数均有良好的负相关关系。     

基于多光谱图像的水稻叶片叶绿素和籽粒氮素含量检测研究

先利用常规技术分析了水稻的叶片叶绿素和籽粒氮素含量,然后用包含绿(G)、红(R)和近红外(NIR)三波段通道的电荷耦合器件(CCD)成像技术对水稻叶片和籽粒进行了无损检测。试验结果显示,水稻叶片叶绿素a、叶绿素b分别与G、NIR通道图像灰度呈极显著线性相关,叶绿素(a+b)含量则与上述两通道图像灰度呈显著线性相关;而且,水稻籽粒氮素含量与G、NIR通道、归一化植被指数(NDVI)灰度呈显著线性相关。由此建立了水稻叶片叶绿素和籽粒氮素含量的多光谱图像预测模型,并分别用21个样本对模型进行检验,其中线性显著相关的7个模型的相对误差RE(%)介于9.36%~157%,实现了对水稻叶片叶绿素和籽粒氮素含量的快速、准确、非破坏性检测。     

基于无人机遥感的花生氮营养反演研究

氮素是影响花生生长发育的重要因素之一,目前传统凯氏定氮法测定步骤繁琐且需要时间较长,而无人 机遥感具有实时、灵活、低成本的特点,因此,为实现对花生氮含量的快速、无损、准确监测,本研究利用大疆精灵4 号无人机搭载的可见光相机,获取不同生育期的可见光影像,运用神经网络算法,建立叶片数字图像彩色信息和叶 片氮含量的关系模型。结果表明,利用数字图像指标作为网络输入向量时,所构建模型的平均绝对偏差为1.5左 右,且以r、g、b(r=R/(R+G+B), g=G/(R+G+B), b=B/(R+G+B))和a, b, c (a=R+G, b=R+B, c=G+B)两种组合参数拟合效果最 好,平均绝对偏差为0.2左右,和真实值相差较小。通过检验发现,两种方法都能准确地预测出花生叶片氮含量,所 构建模型能快速、无损地测定花生植株的肥料状况。     

基于卫星遥感的冬小麦拔节期长势监测

为给小麦调优栽培提供信息支持,利用卫星影像信息结合地面试验数据,通过分析小麦拔节期叶面积指数、生物量以及植株氮素含量三个群体质量指标与植被指数之间的关系,建立了基于归一化植被指数(NDVI)、比值植被指数(RVI)的小麦群体质量指标监测模型.结果表明,NDVI与叶面积指数和植株氮素含量呈现显著的正相关关系(R2分别为0.8483和0.8238),与地上部生物量间的相关性未达显著水平(R2=0.7746).RVI与叶面积指数和植株氮素含量呈线性正相关(R2=0.7651和R2=0.78),而与地上部生物量呈显著线性正相关(R2=0.8277).利用不同的试验数据对所建模型进行了检验,监测值与实测值较为吻合,根均方差(RMSE)分别为0.19、106.13 kg·ha-1和0.136%,显示模型具有较好的监测性和通用性.因此,在拔节期可以利用NDVI对叶面积指数和植株氮素含量进行监测,对地上部生物量的监测则以利用RVI数据较好.     

新植苎麻当年丰产的营养诊断

采取打孔法测定叶片养分,并结合测定土壤肥力进行新麻当年丰产综合营养诊断,初步得出叶片N/KO_2值是一项重要的营养诊断指标;丰产新麻齐苗一封行期短(约9天),为麻株氮素营养最大效率期,消耗土壤养分较大。而封行期以后对钾素的吸收强度增大,因此封行——黑杆期是营养诊断的关键时期。此时土壤水解氮和速效钾应分别在244ppm左右和200ppm以上;同时反映植株N/KO_2值的叶色变化可作为形态诊断的参考。     

有机肥化肥配施的双季晚稻群体冠层光谱特征研究

以不同施肥模式为基础,分析了晚稻群体冠层光谱反射率、一阶微分光谱和归一化光谱特征,并对叶片氮含量、氮积累量、产量、叶面积指数和叶干物质积累进行了相关性分析,构建了以高光谱特征参数为自变量的水稻氮素营养诊断模型。结果表明,叶片氮素含量与665 nm处冠层光谱反射率呈极显著相关性(p0.001),与554 nm和672 nm处的一阶微分光谱也呈极显著相关性(p0.001);以λr构建的指数函数y=684.91e0.028x,决定系数(R2)为0.90、(SDr-SDb)/(SDr+SDb)构建的指数函数y=0.66e0.11x,决定系数(R2)为0.88,均能很好地诊断在有机肥和无机肥配施模式下的水稻氮素营养。     

杂交棉氮素营养诊断指标的初步研究

利用反射仪测定滴灌杂交棉植株硝酸盐含量,研究氮素营养诊断。结果表明,不同生育期的倒4叶叶柄硝酸盐含量与施氮量及产量之间均呈极显著相关。由此确定杂交棉现蕾期、初花期、花铃期和铃期的硝酸盐临界值。分别为17811mg·L^-1、3979mg·L^-1、5980mg·L^-1和4396mg·L^-1,初步确定了杂交棉不同生育期氮素营养诊断指标。     

不同砧木材料嫁接冬瓜苗期氮营养特性综合评价

评价冬瓜砧木的氮素营养效率,解决冬瓜氮肥施用过量的问题.以'铁柱168'为接穗,获得11种嫁接苗,以自根苗为对照,分别在低氮(0.5 mmol/L)和正常氮(14.0 mmol/L)水平下进行水培试验,测定11种砧木材料的嫁接冬瓜苗期的植株干物量、氮含量和氮素累积量等指标.通过主成分分析计算嫁接苗与自根苗在正常氮和低氮...     

基于数字图像特征的冬小麦渍害监测研究

为探索渍害胁迫下冬小麦灾损程度的可视化监测方法,通过田间试验,分析了麦田16个常用图像特征指数在不同受渍时间下的变化特征及其与冬小麦SPAD值、产量和千粒重的相关关系,并建立了基于图像特征指数衰减量的冬小麦渍害估算模型。结果表明,随渍水时间的增加,红光(R)、红光标准化值(NRI)、超红指数(EXR)、植被颜色指数(CIVE)极显著上升,而绿光标准化值(NGI)、归一化绿红差值指数(NGRDI)、绿-红差值指数(GMR)、超绿指数(EXG)、绿红比值指数(GRVI)则极显著下降;且这9个图像特征指数均与冬小麦SPAD值、产量和千粒重呈极显著相关,相关系数的最大绝对值分别为0.92、0.85和0.91;基于图像指数衰减量所建的SPAD值、产量和千粒重减少量的估算模型均以二次多项式最优,且以CIVE指数衰减量构建的SPAD值、产量和千粒重减少量估算模型的预测精度最高,验证集决定系数分别达到0.98、0.95、0.96。因此,数字图像技术可用于冬小麦渍害监测,且以基于CIVE指数的监测效果最佳。     

基于图像处理技术的5种红树林叶片形态特征及叶绿素相对含量的估测

为研究基于计算机视觉的图像处理技术获得的红树林叶片形态特征和叶绿素相对含量,以5种红树林为研究对象,分析其叶片形态特征及建立叶片颜色参数和叶绿素相对含量的回归模型,为苗木培育及营养诊断提供理论依据。结果表明：基于图像处理技术获得红树林叶片形态特征值是可信的,5种红树林叶片形态特征（叶面积、叶长、叶宽、叶周长、叶片形态因子）存在显著差异。红海榄和木榄单片叶片最大,其次是秋茄和桐花树,白骨壤叶片最小,白骨壤叶片形态接近椭圆形,红海榄和秋茄2种红树叶片属于长条型,木榄和桐花树叶片形态类似,红海榄叶长和叶宽相关性最强。5种不同种类红树林的SPAD值和Dualex值差异性显著。利用数码相机获取5种红树林叶片彩色图像,通过图像处理软件提取RGB以及通过差值、比值、标准化值、归一化值等运算组合的28种颜色特征值,与叶绿素相对含量（SPAD值、Dualex 值）进行回归分析,B值与SPAD值极显著相关,(R+B+G)/3、R/B、G/B与SPAD值显著相关;18种颜色特征参数与Dualex值显著相关,其中相关系数最大的为G-B和G值。因此,可依据颜色特征参数（R、G、B）建立相应的统计模型进行红树林叶片叶绿素含量的估测,进而为检测红树林生长、诊断营养状况以及进行水肥精确管理提供理论依据和技术支持。     

Artificial Neural Network Modelling of Leaf Water Potential for Potatoes Using RGB Digital Images: A Greenhouse Study

Plant water status information of potato (Solanum tuberosum L. cv. Russet Burbank) is needed at the farm level for irrigation scheduling. This research investigated the feasibility of using a 5-megapixel digital camera to determine the leaf water potential (Ψ_L) of potato plants by capturing red, green, blue (RGB) digital images in the visible region of the electromagnetic spectrum. A greenhouse experiment was conducted in containerized cv. Russet Burbank potato plants subjected to five soil nitrate-nitrogen (N) levels and four soil water content levels. An artificial neural network (ANN) model, built with RGB images, RGB image transformations, RGB vegetation indices, and principal components analysis, found that for the validation data set, the measured Ψ_L and predicted Ψ_L results were from common populations. Other results showed: (1) a linear trend between soil nitrate-N levels and leaf reflectance in the G image band, (2) that the RG image bands were more suitable than the B image band for classifying leaf pigment from leaf shadow and leaf damage, (3) soil nitrate-N interacted with leaf greenness, affecting Ψ_L prediction, and (4) some image variables were more important than others in the ANN model. Although this greenhouse research shows promise, further field-based research is required to validate the selection of input neurons used and also validate the use of ANN modelling to determine Ψ_L at the plant canopy level with cv. Russet Burbank and other cultivars. In addition, an image acquisition method needs to be developed to obtain periodic representative sample coverage over a field.     

A comprehensive study of plant density consequences on nitrogen uptake dynamics of maize plants from vegetative to reproductive stages

Nitrogen (N) use efficiency (NUE), defined as grain produced per unit of fertilizer N applied, is difficult to predict for specific maize (Zea mays L.) genotypes and environments because of possible significant interactions between different management practices (e.g., plant density and N fertilization rate or timing). The main research objective of this study was to utilize a quantitative framework to better understand the physiological mechanisms that govern N dynamics in maize plants at varying plant densities and N rates. Paired near-isogenic hybrids [i.e., with/without transgenic corn rootworm (Diabrotica sp.) resistance] were grown at two locations to investigate the individual and interacting effects of plant density (low—54,000; medium—79,000; and high—104,000 pl ha⁻¹) and sidedress N fertilization rate (low—0; medium—165; and high—330 kg N ha⁻¹) on maize NUE and associated physiological responses. Total aboveground biomass (per unit area basis) was fractionated and both dry matter and N uptake were measured at four developmental stages (V14, R1, R3 and R6). Both plant density and N rate affected growth parameters and grain yield in this study, but hybrid effects were negligible. As expected, total aboveground biomass and N content were highly correlated at the V14 stage. However, biomass gain was not the only factor driving vegetative N uptake, for although N-fertilized maize exhibited higher shoot N concentrations than N-unfertilized maize, the former and latter had similar total aboveground biomass at V14. At the R1 stage, both plant density and N rate strongly impacted the ratio of total aboveground N content to green leaf area index (LAI), with the ratio declining with increases in plant density and decreases in N rate. Higher plant densities substantially increased pre-silking N uptake, but had relatively minor impact on post-silking N uptake for hybrids at both locations. Treatment differences for grain yield were more strongly associated with differences in R6 total biomass than in harvest index (HI) (for which values never exceeded 0.54). Total aboveground biomass accumulated between R1 and R6 rose with increasing plant density and N rate, a phenomenon that was positively associated with greater crop growth rate (CGR) and nitrogen uptake rate (NUR) during the critical period bracketing silking. Average NUE was similar at both locations. Higher plant densities increased NUE for both medium and high N rates, but only when plant density positively influenced both the N recovery efficiency (NRE) and N internal efficiency (NIE) of maize plants. Thus plant density-driven increases in N uptake by shoot and/or ear components were not enough, by themselves, to increase NUE.     

Identification and evaluation of high nitrogen nutrition efficiency in rapeseed (Brassica napus L.) germplasm

To establish identification and evaluation methods of N (nitrogen) absorption and utilization of rapeseed (Brassica napus L.), difference of N nutrition efficiency (NNE) among rapeseed germplasms and relationship between NNE and plant traits under various N application rates were analyzed in this research. Pot cultivating experiments were conducted to investigate NNE with 3 ​N application rates in soil (0.05, 0.2 and 0.3 ​g/kg). A total of 12 rapeseed germplasms were planted, nitrogen absorption efficiency (NAE) and nitrogen utilization efficiency (NUE) in seedling stage, bolting stage, initial flowering stage, final flowering stage, and maturity stage were obtained. Results showed that bolting stage was the best period for NAE identification and evaluation. Low N application rate in soil (0.05 ​g/kg) was the best for NAE, and the indirect indexes were basal stem diameter, plant root dry weight and above ground plant dry weight. Maturity stage was the best period for NUE identification and evaluation. High N application rate in soil (0.3 ​g/kg) was the best for NUE, and indirect indexes were above ground plant dry weight and basal stem diameter. N application rates of 0.05 ​g/kg in soil was the best for nitrogen harvest index at maturity stage, and indirect indexes was number of pods per plant. Plant traits of rapeseed germplasms affected NNE. Higher basal stem diameter, plant root dry weight and above ground plant dry weight at bolting stage under low N application rate were important characteristics of N absorption in rapeseed. Higher above ground plant dry weight and basal stem diameter at maturity stage under high N application rate were important characteristics of N utilization. Higher number of pods per plant at maturity stage under lowe N application rate was an important characteristic of N harvest index. These results provided a reliable index for N management and provided theoretical basis for guiding rapeseed breeding.     

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.