Quantifying economic losses associated with levels of wheat streak mosaic incidence and severity in the Texas High Plains

Wheat streak mosaic (WSM), caused by the Wheat streak mosaic virus (WSMV), which is transmitted by the wheat curl mite (Aceria tosichella), is the most prevalent virus disease of wheat in the Texas High Plains. Infected plants initially exhibit mosaic symptoms, which lead to severe stunting, complete chlorosis and, in the most severe cases, eventually plant death. Wheat plants infected with WSMV have lower forage and grain yields and exhibit reduced water-use efficiency compared to non-infected plants. The disease impact on water-use efficiency raises an important issue of whether diseased fields should be irrigated as frequently as non-diseased fields. The issue becomes more relevant when energy costs and the dwindling water resources from the Ogallala Aquifer are taken into consideration. This study examined the potential economic losses due to WSM, using data collected from two fields in 2007 and 2009. A hand-held hyperspectral radiometer was used to quantify severity of WSM in multiple 1 m² plots along two transects, each stretching from the edges of the fields to their centers. Grain yield declined exponentially (R² = 0.79, P < 0.0001) with increasing disease severity, as measured by reflectance at 555 nm. For economic analysis, grain yield from each plot was used for determining cost adjustments and linked revenues in relation to WSM severity levels, which allowed calculations of potential profit reduction. The method enables one to compare losses associated with different levels of WSM severity to a baseline with little or no WSMV infection. Results show that losses from the disease are primarily an outcome of reduced revenue due to a decrease in grain yield, and, as expected, losses incurred per unit land area rapidly increase with increasing disease incidence and severity. Furthermore, producers incur additional marginal losses when irrigating fields with WSM because there is little or no return for irrigation inputs, as water-use efficiency of severely diseased wheat is drastically reduced. Results from this study are useful in estimating losses at differing levels of disease incidence and severity and represent the first step in development of an economic threshold for wheat streak mosaic.     

High-Yielding Performance of A New Rice Variety,Ir53650In Mildly Improved Acid Sulfate Soil Conditions

Abstract

A spectral and polarization image observation technique for detecting multiband polarimetric characteristics of reflected light from field-growing plants under daylight conditions was developed and the potential application of the method to in-situ assessments of wheat-leaf orientation at the heading stage was assessed. The developed digital imaging system corresponded to wavelength bands centered at 470, 550, and 647 nm, each with bandwidths of 10 nm. The instrument was fitted with a glass polarizer, which rotated from 0 to 360º in 15º steps, and polarized images of 1360 ×1024 pixels were captured at heading in wheat plots subjected to different fertilizer regimes at the jointing stage. Degree of polarization (DP) and mean brightness (MB) of the three bands were calculated from images of several pairs of top-dressed and non-top-dressed (non-dressed) plots, with a camera depression angle of 15–20º on two clear days. The relative azimuth angles between the view and insolation were approximately 135º (oblique front) and 180º (right in front), respectively. The mean DP for each plot area in the images varied between 0.3 and 1.4%. Although most of the top-dressed plots had significantly higher DPs than the non-dressed plots in the 550 nm band, few of the MB images in any band showed a clear difference between the top-dressed and non-dressed plots.     

Wheat class identification using monochrome images

Wheat class identification by bulk sample analysis using a machine vision method would be helpful for automation of grain handling, binning and shipping operations in grain elevators. A machine vision system with a monochrome camera was used to identify eight western Canadian wheat classes at four moisture levels (11%, 14%, 17% and 20% wet basis) by bulk sample analysis (n=100 images for each group of samples). Grayscale images (1024×768 pixels) of the grain bulk were captured by the monochrome camera, and stored on a data acquisition system. Algorithms were developed to extract 32 textural features automatically from the grayscale images. The mean gray values of the western Canadian wheat classes ranged between 106 and 143, and it was the highest for Canada Prairie Spring Red and the lowest for Canada Western Extra Strong and Canada Western Red Winter. The mean gray values of the wheat samples were significantly higher at 17% moisture content and lower at 11% moisture content among the tested moisture levels (α=0.05). The overall classification accuracies of a quadratic discriminant function were 93.8%, 92.5%, 92.0% and 94.4% when the wheat classes were at 11%, 14%, 17% and 20% moisture contents, respectively. Similarly, the accuracies of a linear discriminant function were 96.1%, 95.0%, 95.4% and 96.3% at 11%, 14%, 17% and 20% moisture contents, respectively. When the wheat classes were identified irrespective of moisture levels (images of the four moisture level grains in each class were mixed together), the accuracy was 89.8% and 85.4% for quadratic and linear discriminant functions, respectively. A monochrome image analysis system has the potential to use for online identification of classes in wheat handling facilities. However, further research is required to determine the performance of the developed method for impurities in bulk grain such as foreign material and dockage.     

基于图像和改进U-net模型的小麦赤霉病穗识别

为了快速、有效地监测小麦赤霉病的发生情况,利用数码相机对人工接种赤霉病菌的小麦田进行RGB图像获取,在图像预处理基础上,利用深度学习网络U-net来对人工标记好的发病麦穗图像进行训练。通过深度学习数据集的构建与测试,建立了基于RGB图像和改进U-net网络模型的小麦赤霉病识别与监测模型,并对模型识别结果进行了验证。结果表明,U-net可以很好地提取图像波段信息,但对于比较复杂的麦穗图像,在使用Keras方法进行图像语义分割时,需要对U-net网络结构进行改进,即在下采样部分加入Dropout层。与人工标记结果相比,模型识别结果的一致性较好,具有较高的监测精度。该模型平均精度为0.969 4,损失函数值为0.075 9,平均交并比MIoU为0.799。上述结果说明改进的U-net模型可以很好地识别和监测小麦图像中的发病麦穗,并在发病麦穗的分割上具有很好的效果     

基于叶片高光谱特征的小麦白粉病严重度估算模式

为了解白粉病胁迫下小麦叶片特征并预测其危害程度,基于大田小区和温室盆栽小麦白粉病接种试验,采用高光谱仪测定受白粉病不同程度危害的冬小麦叶片光谱反射率,并分析光谱特征参数与白粉病严重度间的关系。结果表明,随着小麦白粉病病情的加重,在可见光350~700nm波段内,叶片光谱反射率增加;而在700~1050nm近红外波段内,叶片光谱反射率明显降低。400~500nm和610~690nm为光谱敏感波段,在650~680nm波段相关系数最高(r0.75)。光谱参数MCARI、PSRI、VARIgreen和AI对叶片病害严重度拟合效果较好,决定系数(R2)变化范围为0.77~0.82,标准误差为9.34~10.14。模型检验表明,小麦单叶片病害严重度超过10%时,检验结果较为理想,单叶片病害严重度低于10%时,则定量估算误差偏大,10%严重度可作为光谱法识别小麦白粉病的临界值。光谱参数MCARI和VARIgreen对小麦白粉病反应敏感,估算误差较小,可作为小麦白粉病严重度的最佳估算模型。     

Investigation of fungal development in maize kernels using NIR hyperspectral imaging and multivariate data analysis

Near infrared (NIR) hyperspectral imaging and hyperspectral image analysis were evaluated for their potential to track changes in fungal contamination on and fungal activity immediately under the surface of whole maize kernels (Zea mays L.) infected with Fusarium verticillioides. Hyperspectral images of clean and infected kernels were acquired using a SisuChema hyperspectral pushbroom imaging system with a spectral range of 1000–2498 nm at predetermined time intervals after infection. Background, bad pixels and shading of acquired absorbance images were removed using exploratory principal component analysis (PCA). When plotting PC4 against PC5, with percentage sum of squares (%SS) 0.49% and 0.34%, three distinct clusters were apparent in the score plot and this was associated with degree of infection. Loading line plots, with prominent peaks at 1900 nm and 2136 nm, confirmed that the source of variation was due to changes in starch and protein. Partial least squares (PLS) regression models, with time as the Y variable, were calculated and also indicated that changes over time were apparent. Variable importance plots (VIP) confirmed the peaks observed in the PCA loading line plots. More systematic future experiments are needed to confirm this, but it can already be concluded that early detection of fungal contamination and activity is possible.     

Estimates of sample size for detection and estimation of incidence and severity of corky ringspot of potato

A computer program was developed to simulate the random collection of tuber samples from potato fields with corky ringspot (CRS). Tubers were harvested from 16 plots in the 1993–94 and 1994–95 seasons, and the incidence and severity of CRS symptoms were assessed. Inputs for the program were number of healthy and CRS-affected tubers and severity tuber symptoms from each plot. The output was the mean and the standard error of the mean of disease incidence and severity for 12 different sample sizes. Accuracy and precision for each sample size were estimated to determine sample size. The sample size of 20 tubers was required to detect the presence of CRS in research plots. The binomial distribution was used. With sample sizes greater than 20, the increase in accuracy and precision leveled off regardless of disease incidence and severity values; therefore sample sizes greater than 20 may be unwarranted for evaluation of chemical control tests.     

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。     

图像处理技术在冬小麦叶面积指数测定中的应用

为了探讨利用图像处理技术测定冬小麦叶面积指数的可行性,在室外光照条件下．固定数码相机高度垂直拍摄冬小麦群体图像,利用图像处理技术获取小麦冠层的图像叶面积指数(ILAI),并用手工测量获得小麦群体实际叶面积指数(LAI),建立ILAI和LAI间与施肥处理有关的关系模型,对该模型的稳定性和实用性进行统计检验。试验结果表明,利用图像处理技术通过ILAI获取小麦LAI是可行的,且简便易行,测量精度和效率都很高。     

Nematodes and fungal diseases in barley and wheat on Prince Edward Island

A total of 31 genera and 28 species of plant and soil nematodes were identified from 30 commercial fields each of barley and wheat on Prince Edward Island. Root-lesion nematodes, primarily Pratylenchus penetrans, were the dominant plant parasites, and the only endoparasitic nematodes recovered from roots. Root-lesion nematodes were the dominant genus in soil, but stunt nematodes (Tylenchorhynchus spp., primarily T. dubius, and Merlinius spp.), and pin nematodes (Paratylenchus spp.) were also recovered frequently. Common root rot, barley net blotch, and wheat leaf blotch, incited by Cochliobolus sativus, Pyrenophora teres, and Leptosphaeria nodorum, respectively, were prevalent in barley and wheat. The nematicide aldicarb reduced the numbers of root-lesion nematodes in roots and soil in experimental plots during 1984–1987, except from soil in wheat and barley in 1984 and in barley in 1986. Aldicarb treatments also increased grain yields significantly by 10% and 19% in 1984 and 1987, respectively. Aldicarb treatments did not affect the incidence of common root rot, barley net blotch, or wheat leaf blotch disease. Correlation and regression analyses of data from experimental plots did not indicate any significant relationships between population levels of root-lesion nematodes in roots or soil and severity of root or foliar diseases in barley or wheat.     

Economics of foliar fungicides for hard red winter wheat in the USA southern Great Plains

Grain yields of winter wheat (Triticum aestivum L.) in the southern Great Plains are often reduced by the presence of foliar diseases. This study was conducted to determine whether the application of foliar fungicides is an economically optimal management strategy. The effects of fungicide treatment on commercially available hard red winter wheat varieties with differing levels of genetic resistance (i.e., resistant, intermediate, and susceptible) to foliar diseases were investigated at two locations, Apache and Lahoma, OK, USA, for the harvest years 2005–2012. Two fungicides were rotated between the two locations and applied at approximately Feekes growth stage 9–10.5. When averaged across years, plots to which fungicide was applied generated greater average net returns than plots that did not receive fungicide for susceptible varieties at Apache, and for resistant, intermediate, and susceptible varieties at Lahoma. However, foliar fungicide application was not economical in every year at either location suggesting fungicide use should be reassessed each year given that profitability depends on year specific yield potential, prices, and foliar disease conditions. At both locations high disease incidence occurred in all but one site-year when the average March through May relative humidity exceeded 65%. Additional research would be required to determine the relationship between weather, including relative humidity, and disease incidence, and to develop an economic threshold for treatment decision aid.     

Survival ofHelminthosporium solani in soil andin vitro colonization of senescent plant tissue

Silver scurf, caused byHelminthosporium solani, is considered to be a tuberborne disease of potato. The ability ofH. solani to overwinter in soil was evaluated in field studies at two locations in New York during 1992. Field plots were established at sites whereH. solani infected potatoes had been produced in 1991. Plants produced from pathogen-free tubers of four cultivars yielded tubers infected with silver scurf at both locations. Up to 61% of tubers were infected in some plots. The ability ofH. solani to colonize leaf tissue was evaluated inin vitro assays. Detached leaves of ten crops were sprayed with a spore suspension ofH. solani and incubated for 20 days.H. solani colonized and sporulated on senescent leaf tissue of alfalfa, sorghum, rye, oats, corn and wheat, and only colonized senescent tissue of rapeseed, red clover and buckwheat. No growth was observed on potato leaf tissue. These results indicate that soil survival and saprophytic ability may be important in the epidemiology of silver scurf of potato.     

基于无人机多时相遥感影像的冬小麦产量估算

为高效准确地预测小麦产量,以浙江省冬小麦为研究对象,利用四旋翼无人机精灵4多光谱相机获取冬小麦5个关键生育时期（拔节期、孕穗期、抽穗期、灌浆期、成熟期）的冠层多光谱数据,选取多光谱相机的五个特征波段计算各生育时期的72个植被指数,分别通过逐步多元线性回归（SMLR）、偏最小二乘回归（PLSR）、BP神经网络（BPNN）、支持向量机（SVM）、随机森林（RF）构建不同生育时期的产量估算模型,最后采用决定系数（R）、均方根误差（RMSE）和相对误差（RE）对估算模型进行评价,筛选出最优估算模型。结果表明,基于随机森林建立的模型估算效果最优,SMLR、PLSR和SVM三种方法建立的模型估算效果接近。利用随机森林算法所建拔节期、孕穗期、抽穗期、灌浆期、成熟期模型的R、RMSE和RE分别为0.92、0.35、11%;0.93、0.33、10%;0.94、0.32、9%;0.92、0.36、9%;0.77、0.67、33%。模型验证时,抽穗期估算效果最好（R、RMSE和RE分别为0.91、0.35和15%）,拔节期、孕穗期、灌浆期估算效果接近且有很好的估算能力,成熟期估算精度最差（R、RMSE和RE分别为0.71、0.47和13%）。由此说明,结合机器学习算法和无人机多光谱提取的植被指数可以提高小麦产量估算效果。     

Yield and quality losses caused by common rust (Puccinia sorghi Schw.) in sweet corn (Zea mays) hybrids

Yield and quality of fresh ears were measured in field plots of selected hybrids of sweet corn (Zea mays L.) that were affected by rust (Puccinia sorghi Schw.) or were nearly rust-free (mancozeb-sprayed). In 1978, 28 hybrids were tested. Losses in total yield ranged from zero in the more resistant entries to nearly 50% in more susceptible entries. In 1979, three cultivars were planted. Yield losses of these cultivars were similar in ranking order to those in 1978, although the loss was greater in late-planted plots because of the greater final severity of the disease. Losses in total yield in late-planted sweet corn were 18%, 26% and 49% for cv. Sugarloaf (most resistant), cv. Jubilee (intermediate) and cv. Style Pak (most susceptible), respectively.     

小麦腥黑穗病研究进展

腥黑穗病是威胁全球小麦生产的重要病害之一,其流行导致小麦大幅度减产乃至绝收,并且由于其病菌的生存能力顽强,更加剧了危险程度。本文从小麦腥黑穗病国内外发病历史、近年来流行危害情况、病原菌及其毒性小种和抗性种质研究进展等方面进行了综述,重点对抗源材料和抗性基因的研究与利用进行了综述和分析。通过系统的分析认为,国外对该病给予了特别的关注,进行了较为全面、深入的研究,对持久控制起到了促进作用;国内的研究明显不足,特别在抗源材料研究、抗性基因开发利用方面处于较严重的滞后状态。通过对近年来国内其他省份和甘肃省的病情变化态势综合分析发现,跨区、跨省种子调运和农户间的交换,加剧了该病的流行危害,目前呈加重流行态势。建议加强抗性材料的储备、抗源筛选以及防治技术和抗病育种研究。     

小波特征与传统光谱特征估测冬小麦条锈病病情严重度的对比研究

为探讨通过小波特征监测小麦条锈病发病程度的可行性,利用连续小波变换提取的小麦冠层光谱350~1 300 nm范围内的9个小波特征和传统光谱特征（植被指数、一阶微分变换特征和连续统特征）,借助偏最小二乘回归（PLSR）建立反演模型,分别将传统光谱特征（SFs）、小波特征（WFs）及传统光谱特征与小波特征结合(SFs & WFs）作为模型的输入,对小麦条锈病病情进行反演。结果表明：（1）小波特征与条锈病严重度的相关性比传统光谱特征强;（2）基于小波特征的模型估测精度（R为0.837）优于基于传统光谱特征的模型估测精度（R为0.824）;（3）传统光谱特征与小波特征结合的模型精度最高,R为0.876,RMSE仅为0.096,因而传统光谱特征与小波特征相结合能够更好地对小麦条锈病病情严重度进行估测。     

Effect of plant density on toxigenic fungal infection and mycotoxin contamination of maize kernels

Field experiments were set up from 2001 to 2004 in North West Italy to determine the effects of plant density on the susceptibility of medium and medium-late maturity maize hybrids to ear rot and to mycotoxin contamination in natural infection conditions. The ears were rated for the incidence and severity of disease symptoms at harvest and the harvested kernels were analysed for mycotoxin fumonisin B₁, zearalenone, deoxynivalenol, aflatoxin B₁ and ochratoxin A.     

基于Sentinel-2多光谱数据和机器学习算法的冬小麦LAI遥感估算

为了丰富大田尺度下冬小麦叶面积指数的遥感估算方法并提高估算精度,以关中地区冬小麦为对象,基于Sentinel-2多光谱卫星数据与地面同步观测的冬小麦叶面积指数样点数据,应用偏最小二乘回归(PLSR)、反向传播神经网络(BPNN)和随机森林(RF)法构建冬小麦叶面积指数估算模型,进行区域冬小麦叶面积指数遥感反演。结果表明,Sentinel-2多光谱卫星影像中心842nm近红外B8波段与冬小麦叶面积指数相关性最好,样本总体相关系数为0.778;植被指数中反向差值植被指数(IDVI)与冬小麦叶面积指数相关性最好,样本总体相关系数为0.776。各种估算模型中LAI-RF模型预测效果最佳,r~2为0.72,RMSE为0.53,RE为16.83%。基于LAI-RF估算模型,应用Sentinel-2多光谱卫星数据较好地反演了研究区冬小麦叶面积指数区域分布,其结果总体上与地面真实情况接近,说明以Sentinel-2卫星影像数据建立LAI-RF估算模型,可应用于区域冬小麦LAI反演制图。     

Growing Brassica juncea as a cover crop, then incorporating its residues provide complementary control of Rhizoctonia root rot of sugar beet

Biofumigation is increasingly viewed as a potentially useful technique for controlling soil-borne crop pathogens, but its efficacy has not systematically been demonstrated at field scale. We investigated the differences in efficacy observed in the field, by analysing the mechanisms by which a Brassica cover crop can act as a biofumigant crop in the prevention of soil-borne disease development. We hypothesised that the biofumigant crop might have a negative effect on soil-borne pathogens whilst growing, and that the pulverisation of this crop and the incorporation of its residues into the soil may enhance this effect. We tested this hypothesis by carrying out three field experiments in 2006, 2007 and 2008 in which Brassica juncea (brown mustard) was managed in different ways within a sugar beet–winter wheat rotation and analysing effects on sugar beet root rot caused by Rhizoctonia solani. Three treatments were studied: mustard pulled out at flowering (MP), mustard crushed at flowering and incorporated into the soil (MC) and bare soil (BS) as a control. We assessed the effect of each treatment on root rot incidence and severity at harvest. Over the 3 years of the experiment, disease incidence was significantly higher on BS plots than on the other plots and was significantly higher on MP plots than on MC plots. MC treatment gave a significantly lower mean conditional severity (severity calculated for diseased beets only) than the BS and MP treatments. Mustard residue incorporation was consistently effective at decreasing disease incidence from year to year (43, 44 and 47% efficacy, as determined by comparison with the disease incidence on BS plots, in 2006, 2007 and 2008, respectively), but the efficacy of growing mustard was variable (36, 16 and 39% efficacy in 2006, 2007 and 2008, respectively). These findings provide insight into the mechanisms by which biofumigant crops may affect soil-borne diseases. These findings have implications for the possible use of biofumigant crops as a biological method for controlling soil-borne diseases at the field scale.     

Aggressiveness variation of Fusarium graminearum isolates from Argentina following point inoculation of field grown wheat spikes

Aggressiveness variation among isolates of Fusarium graminearum from Argentina was analyzed by following disease development on point inoculated spikes of field grown wheat. Two aspects of the capacity of the isolates to induce disease were observed: (i) the infection efficiency reflected by the ability to produce symptoms and evaluated as the number of symptomatic spikes over the inoculated ones; and (ii) the size of the lesion provoked, which is reflected by the number of symptomatic spikelets over its total number. One hundred and twelve isolates were found to induce significantly different levels of disease severity, reflecting variation in aggressiveness. Differences were also found between the isolates for the thousand kernel weight (TKW) and the area under the disease progress curve (AUDPC) and the correlations between disease severity, AUDPC, and TKW were highly significant. Based on disease severity, isolates were clustered as low, medium and highly aggressive and both lesion size and infection efficiency were significantly different between these groups. The movement of the pathogen in the spike occurred primarily downwards the point of inoculation. Movement toward the upper portion was related with the aggressiveness of the isolates and the premature ripening of the spike appeared to be a function of isolate aggressiveness. In this work point inoculation allowed us to study not only the aggressiveness of a large collection of F. graminearum isolates but also to analyze the development of Fusarium head blight symptoms in large numbers of spikes under conditions similar to those in which this disease naturally occurs.