基于LS-SVM的草莓固酸比和可滴定酸近红外光谱定量模型

为提高草莓固酸比和可滴定酸近红外光谱定量模型的性能,该文采用偏最小二乘法提取的潜在变量作为最小二乘-支持向量机模型的输入变量,建立了两指标的近红外定量模型,并与偏最小二乘模型结果进行了比较,建模所使用的光谱范围为6000～12500 cm-1。结果表明,草莓可滴定酸和固酸比偏最小二乘模型校正相关系数、校正和预测均方根误差分别为0.430、0.096%、0.096%及0.688、0.926和1.190,而两指标的前10个潜在变量得分作为输入变量的最小二乘—支持向量机模型各项性能均远优于偏最小二乘模型,其校正和预测相关系数、校正和预测均方根误差以及剩余预测偏差分别为：可滴定酸0.965、0.967、0.028%、0.027%、3.881;固酸比0.980、0.973、0.258、0.373、3.111。研究表明,潜在变量作为最小二乘支持向量机模型的输入变量可在较大程度上改善草莓可滴定酸和固酸比指标近红外定量模型的预测性能和稳定性。     

基于无人机高光谱的冬小麦氮素营养监测

为了实现小区域尺度上的作物氮素营养状况遥感监测,该研究利用无人机搭载Cubert UHD185成像光谱仪对2016 -2017年关中地区的冬小麦进行遥感监测,通过分析冠层光谱参数与植株氮含量、地上部生物量和氮素营养指数的相关性,筛选出对三者均敏感的光谱参数,结合多元线性逐步回归、偏最小二乘回归和随机森林回归建立抽穗期冬小麦氮素营养指数（Nitrogen Nutrition Index,NNI）估测模型,并与单个光谱参数建立的冬小麦氮素营养指数模型进行比较。结果表明,任意两波段光谱指数对氮素营养指数更为敏感,与氮素营养指数均达到了极显著性相关;基于差值光谱指数和红边归一化指数的单个光谱参数构建的模型具有粗略估算氮素营养指数的能力,相对预测偏差分别为1.53和1.56;基于随机森林回归构建的多变量冬小麦氮素营养指数估算模型具有极好的预测能力,模型决定系数为0.79,均方根误差为0.13,相对预测偏差为2.25,可以用来进行小区域范围内的冬小麦氮素营养指数遥感填图,为冬小麦氮素营养诊断、产量和品质监测及后期田间管理提供科学依据。     

结合SPA和PLS法提高冬小麦冠层全氮高光谱估算的精确度

【目的】 冠层高光谱全波段信息可以在小麦拔节期快速无损地估算叶片的氮含量。本研究结合连续投影算法 (SPA) 和偏最小二乘 (PLS) 技术,筛选了冬小麦拔节期冠层光谱对叶片氮含量的敏感特征波段,以期为冬小麦关键生育期氮素含量的遥感估算提供理论依据和技术支持。 【方法】 以陕西关中地区2015—2016年冬小麦小区试验为基础,基于连续投影算法 (SPA) 提取冬小麦叶片全氮含量的冠层光谱敏感波段,并结合偏最小二乘 (PLS) 回归法建立基于敏感特征波段的冬小麦拔节期叶片氮含量估算模型。 【结果】 SPA算法从冬小麦338～2510 nm的冠层光谱中优选出了1985 nm、2474 nm、1751 nm、1916 nm、2507 nm、1955 nm、2465 nm和344 nm共计8个叶片全氮含量的敏感特征波段,波段数目下降了98.9%,有效降低了光谱信息的冗余;基于敏感特征波段构建的叶片氮含量偏最小二乘回归模型的决定系数和均方根误差分别为0.82和0.28,模型验证方程的决定系数和均方根误差分别为0.84和0.21,模型的相对预测偏差大于2,具有较高的精度和良好的预测能力。 【结论】 与常用植被指数的叶片氮含量估算模型相比,连续投影算法 (SPA) 结合偏最小二乘 (PLS) 方法的叶片氮含量估算精度更高,稳定性更强,可以作为冬小麦拔节期叶片氮含量的高光谱估算方法。      

基于高光谱和BP神经网络的玉米叶片SPAD值遥感估算

为了进一步提高玉米叶绿素含量的高光谱估算精度,该文测定了西北地区玉米乳熟期叶片的光谱反射率及其对应的叶绿素相对含量（soil and plant analyzer development,SPAD）值,分析了一阶微分光谱、高光谱特征参数与 SPAD的相关关系,构建了基于一阶微分光谱、高光谱特征参数和 BP 神经网络的 SPAD 估算模型,并对模型进行验证;再结合主成分回归（principal component regression,PCR）、偏最小二乘回归（partial least squares regression,PLSR）以及传统回归模型与 BP 神经网络模型进行比较。结果表明：SPAD 值与一阶微分光谱在763nm 处具有最大相关系数（R=0.901）;以763 nm 处的一阶微分值、蓝边内最大一阶微分为自变量建立的传统回归模型可用于玉米叶片 SPAD 估算;将构建传统回归模型时筛选到的光谱参数作为输入,实测 SPAD 值作为输出,构建 BP 神经网络模型,其建模与验模 R2分别为0.887和0.896,RMSE 为2.782,RE 为4.59%,与其他回归模型相比,BP 神经网络模型预测精度最高,研究表明 BP 神经网络对叶绿素具有较好的预测能力,是估算玉米叶片 SPAD 值的一种实时高效的方法。     

基于EPO算法去除水分影响的土壤有机质高光谱估算

野外进行土壤有机质的光谱快速预测时需考虑土壤含水量的影响。在室内设计人工加湿实验分别获取9个土壤含水量梯度(0~32%,间隔4%)的土壤光谱数据,分析土壤含水量变化对光谱的影响,再利用外部参数正交化法(external parameter orthogonalization,EPO)进行湿土光谱校正,并结合偏最小二乘回归和支持向量机回归分别建立土壤有机质预测模型。结果表明,土壤光谱反射率随着土壤含水量的增加呈非线性降低趋势,偏最小二乘回归模型的预测偏差比为1.16,模型不可用;经EPO算法校正后,各土壤含水量梯度之间的光谱差异性降低,能实现土壤有机质在不同土壤含水量梯度的有效估算,偏最小二乘回归和支持向量机回归模型的预测偏差比分别提高至1.76和2.15。研究结果可为田间快速预测土壤有机质提供必要参考。     

金银花贮藏过程中绿原酸含量的高光谱无损检测模型研究

绿原酸(chlorogenicacid,CGA)是评价金银花品质的重要指标。为了实现金银花贮藏期间CGA含量变化的快速有效检测,该文采集了500个不同贮藏时间(0～20d)的金银花高光谱图像,构建CGA含量的高光谱检测模型。为了提高模型性能,采用savizky-golay卷积平滑(SG),移动窗口平滑(moving average),标准正态变量(standard normal variable,SNV),基线校正(baseline correction,BC),多元散射校正(multiplicative scatter correction,MSC),正交信号校正(orthogonal signal correction,OSC)6种预处理方法并建立偏最小二乘回归(partial least squares regression,PLSR)模型,确定SNV方法为最佳预处理方法,其预测集的R2为0.976 6,RMSE为0.271 1%。为了简化校准模型,利用无信息变量消除(uninformative variable elimination,UVE),连续投影算法(successive projections algorithm,SPA),竞争性自适应加权算法(competitive adaptive reweighted sampling,CARS)以及UVE-CARS、UVE-SPA等方法对SNV预处理后的光谱提取特征波长。然后,分别基于全光谱数据和所选特征变量数据,建立线性偏最小二乘回归(PLSR)和非线性BP神经网络模型。结果表明:UVE-CARS算法可以有效地减少提取变量个数(共提取26个,仅占全光谱范围的3.2%),PLSR和BP模型的预测集R2分别为0.974 6和0.978 4,RMSE分别为0.286 3%和0.250 3%。非线性BP模型预测结果整体优于线性PLSR模型,在BP模型中,UVE-CARS-BP预测精度最高,预测集的R2和RMSE的值分别为0.978 4, 0.250 3%。综上,基于高光谱成像技术建立的SNV-UVE-CARS-BP模型,可以实现金银花贮藏过程中CGA含量变化的快速无损预测。     

电子舌预测不同体积分数牛奶的表观黏度

该文为建立牛奶的电子舌响应信号与其表观黏度的关系,在单因素方差分析和主成分分析的基础上,提出了比较多元线性回归、逐步多元线性回归和偏最小二乘回归3种模型对牛奶表观黏度的预测效果的方法。结果显示,单因素方差分析表明体积分数对牛奶的表观黏度和各个传感器响应信号都具有极显著性的影响;主成分分析（PCA）可以用来区分牛奶的5种不同体积分数;偏最小二乘回归模型预测效果最好,模型预测值与实际值的相关系数R达到0.9659,平均相对误差（MRE）和预测均方根误差（RMSEP）分别为4.5499%和8.4645×10-5,建模最佳主成分数为3。研究结果表明,偏最小二乘回归模型是电子舌预测牛奶表观黏度的有效方法,该方法为牛奶表观黏度的科学研究提供参考。     

应用红外光声光谱技术及支持向量机模型测定土壤有机质含量

快速测定土壤有机质含量对作物生产和土壤肥力评价具有重要意义,红外光声光谱技术的应用为土壤有机质快速测定提供了可能。本研究以江苏省南京市溧水区水稻土土样为材料,探究了红外光声光谱技术在有机质测定中的应用。采用主成分分析、偏最小二乘和独立成分分析,分别提取了土壤光谱的主成分、偏最小二乘潜变量和独立成分,并以提取的信息输入支持向量机,从而构建了三种支持向量机校正模型。同时,偏最小二乘也被用于建立校正模型,作为支持向量机模型的对照。预测结果表明,基于独立成分的支持向量机模型效果最好,预测相关系数R2、均方根误差RMSEP和实际测量值的标准差与光谱模型预测值标准差的比值即RPD值分别为0.808、0.575和2.28。F检验表明,该模型显著优于基于主成分的支持向量机模型,但与基于偏最小二乘潜变量的支持向量机模型,以及经典偏最小二乘模型没有显著差异。t检验表明,各校正模型对有机质的预测结果与化学测定结果没有显著差异。因此,红外光声光谱技术为土壤有机质的快速测定提供了新的技术手段。     

ASD Field Spec3野外便携式高光谱仪诊断冬小麦氮营养

氮素营养诊断关键在于氮营养指数(nitrogen nutrient index,NNI)预测。对于冬小麦氮营养指数预测模型而言,如何选取预处理方法和建模方法不一而足,不同预处理和模型选取对预测结果精度的影响程度目前还不清楚。该研究以ASD Field Spec3野外便携式高光谱仪采集乐陵市冬小麦冠层高光谱数据,采用10种光谱预处理方法并结合3种模型(偏最小二乘回归、BP神经网络和随机森林算法)建立多种冬小麦氮营养指数高光谱预测模型。对比模型预测精度表明最佳的高光谱建模方法为随机森林算法结合SG卷积平滑预处理所建模型(预测集R2=0.795,RMSE=0.125,RE=11.7%)精度高、可靠性强,是筛选出最佳的冬小麦氮营养指数高光谱预测模型。该研究结果对冬小麦氮营养指数高光谱预测建模具有科学价值,为筛选最优高光谱预处理方法和预测模型提供技术参考。     

新疆艾比湖湿地土壤有机碳含量的光谱测定方法对比

干旱半干旱地区湿地土壤中的有机碳是影响土壤质量,制约植物生长的重要因素之一,其含量的变化会影响生态系统的安全和稳定。为快速估测湿地土壤有机碳含量,在新疆艾比湖湿地保护区采集140个荒漠土壤样品,利用土壤可见/近红外光谱数据以及化学分析获取的土壤有机碳数据,在对土壤原始光谱反射率进行卷积平滑的基础上,获取了一阶微分、倒数对数一阶微分2种光谱预处理指标,采用蚁群-区间偏最小二乘法、基于支持向量机的回归特征消去法,选择土壤有机碳含量近红外光谱特征波长,在此基础上构建土壤有机碳含量偏最小二乘回归、支持向量回归模型。结果表明:1)利用原始一阶微分建立的模型,预测能力优于倒数对数一阶微分建立的模型。2)4种建模结果比较显示,利用原始一阶微分经基于支持向量机的回归特征消去法进行特征变量选择后建立的土壤有机碳含量模型,预测精度最高。训练集的相关系数以及均方根误差分别为0.9687、0.158%;测试集的相关系数和均方根误差分别为0.9091以及0.268%。因此,经过卷积平滑以及一阶微分预处理、并利用基于支持向量机的回归特征消去法建立的模型具有较高的预测精度和较好的稳健性,可以作为有效手段估算荒漠湿地土壤有机碳含量。     

灌溉制度对膜下滴灌甜菜产量及水分利用效率的影响

为制定新疆合理的甜菜膜下滴灌制度,设置3个灌水次数(8、9和10次)和2个灌水定额(45和60mm)两因素全组合试验,于2016—2017年在新疆玛纳斯县农科院甜菜改良中心开展田间试验。结果表明,灌水次数增加时甜菜叶面积指数与产量增加,含糖率降低,对甜菜的水分利用效率、耗水量无明显影响(P0.05),甜菜叶绿素值随灌水次数与定额增加呈下降趋势;在灌水次数与定额交互作用下,灌水8次时由于土壤相对含水率低于50%,甜菜会减产;当灌水9次,灌水定额为45 mm时,增加15 mm灌水定额土壤相对含水率达50%以上,此时甜菜增产7.4%～7.7%,糖产增加9.4%～9.7%;而继续增加灌水次数时,会导致甜菜含糖率降低而降低糖产。因此针对新疆膜下滴灌甜菜以60 mm灌水定额灌水9次为宜,可获得高产与糖产,较传统新疆膜下滴灌甜菜制度节水10%。该研究对指导新疆膜下滴灌甜菜灌溉制度具有一定意义。     

氮肥施用量对高产甜菜纤维根系分布及活力的影响

为了解施N肥对甜菜生长的影响规律。在田间条件下,研究了不同施N量（0、90、180、270、360 kg/hm2）对甜菜（KWS2409）纤维根系生长、分布和活力变化的影响。结果表明,施N比对照增加浅层侧根数、外层和深层纤维根干重及100 cm土层纤维根总干重,并提高各生育期侧根和主根活力。其中,100 cm土层最大纤维根干重施N 比对照增加了60.4%～168.4%,最大侧根数增加了22.7%～75.1%,且以0—20 cm和40—60 cm深的外土层及80—100 cm深的内土层纤维根系增加较大,分别比对照增加了129.6%～266.8%、71.0%～234.0%和101.5%～202.8%。主根伤流液量和侧根的活力分别比对照增加了56.2%～89.9%、23.7%～63.4%。N 180 kg/hm2处理0—100 cm土层中纤维根总量、各土层中根量最大,各生育时期主根和侧根活力最强,块根产量（82609.63 kg/hm2）和产糖量（13892.64 kg/hm2）均最高,而含糖率（16.83%）较N0处理（18.34%）略降。说明合理施N量有利于甜菜纤维根系生长和提高产糖量。     

Potassium efficiency mechanisms of wheat,barley, and sugar beet grown on a K fixing soil under controlled conditions

Plant species differ in their potassium (K) efficiency, but the mechanisms are not clearly documented and understood. Therefore, K efficiency of spring wheat, spring barley, and sugar beet was studied under controlled conditions on a K fixing sandy clay loam. The effect of four K concentrations in soil solution ranging from low (5 and 20 μM K) to high (2.65 and 10 mM K) on plant growth and K uptake was investigated at 3 harvest dates (14, 21, and 31 days after sowing). The following parameters were determined: shoot dry matter (DM), K concentration in shoot dry matter, root length (RL), root length/shoot weight ratio (RSR), shoot growth rate/average root length ratio (GR_s/aRL), K influx, and soil solution K concentrations. Wheat proved to have a higher agronomic K efficiency than barley and sugar beet, indicated by a greater relative yield under K‐deficient conditions. As compared to both cereals, sugar beet was characterized by higher K concentrations in the shoot dry matter, only 30—50 % of the root length, 15—30 % of the RSR and a 3 to 6 times higher GR_s/aRL. This means that the shoot of sugar beet had a 3 to 6 times higher K demand per unit root length. Even at low K concentrations in the soil solution, sugar beet had a 7 to 10 times higher K influx than the cereals, indicating that sugar beet was more effective in removing low available soil K. Wheat and barley were characterized by slow shoot growth, low internal K requirement, i.e. high K utilization efficiency, and high RSR, resulting in a low K demand per unit root length. At low soil K concentrations, both cereals increased K influx with age, an indication of adaptation to K deficiency. The mechanism of this adaptation merits closer investigation. Model calculations were performed to estimate the K concentration difference between the bulk soil and the root surface (ΔC_L) needed to drive the measured K influx. For the two cereals, the calculated ΔC_L was smaller than the K concentration in the soil solution, but for sugar beet, ΔC_L was up to seven times higher. This indicates that sugar beet was able to mobilize K in the rhizosphere, but the mechanisms responsible for this mobilization remain to be studied.     

Sugar beet yield response to different levels of saline irrigation water and leaching in an arid region

The main objective of this work was to evaluate the effects of saline irrigation water and leaching on the sugar beet yield components. In a field experiment in Rudasht region (Isfahan, Iran), three irrigation water salinity levels (1.6, 8.1, and 12.3 dS m^?1) and with/without leaching were applied. The experimental units comprised of a completely randomized block design, with split plot in four replications. The results indicated that the white sugar yield and alkalinity decreased by increasing the water salinity. Salts leaching significantly increased the root yield, white sugar yield, and white sugar concentration. With higher levels of water salinity molasses sugar, leaf weight, and the concentrations of Na, K, and α- amino-N in sugar beet significantly increased. Consequently, it appears that the use of drainage water in combination with fresh water could be recommended as a strategic management way to grow sugar beet in the investigated arid region.     

Mild salinity improves sugar beet (Beta vulgaris L.) quality

Abstract

Sugar beet (Beta vulgaris L.) is cultivated mainly on saline soils. Low levels of salinity stimulate growth of this crop plant possibly due to production of broader leaves as sources of assimilates. In this work, six cultivars were studied under mild salinity (EC = 5.5 dS m^?1) in a field experiment to analyse its effect on growth parameters and yield of storage root and sugar accumulation. An attempt was also made to determine the contributing role of photosynthetic gas exchange in response of sugar beet plants to salinity. Production of greater leaf area in salinized plants occurred only transitionally in the early growth period; in progression of the growing season it was decreased, and at 3rd harvest (100 days after treatment) it was significantly lower compared with control plants without cultivar differences. Leaf chlorophyll fluorescence, net photosynthesis rate, and stomatal conductance did not change by salinity significantly. Although, at the end of growth season, leaf area and potential photosynthesizing component of salinized plants on the basis of leaf area (LAR) or weight (LWR) were significantly lower than for control plants, weight of storage root and sugar content were up to 90 and 37% higher than in control plants, respectively. Consequently, a considerable higher yield under mild salinity conditions in sugar beet is not attributable to higher leaf area or, therefore, higher photosynthetic capacity of whole plants. Indeed, the storage roots benefit from lower dry matter and surface production of shoot during the late growing season (because of lower nitrogen assimilation and a slight drought stress of salinized plants) and a change in dry-matter partitioning in favor of roots takes place. However, a possible special effect of Na on carbon allocation for storage and structure and involvement of growth regulators in the change of root-shoot allometry could not be excluded.     

Efficiency of Potassium Fertilization and Salicylic Acid on Yield and Nutrient Accumulation of Sugar Beet Grown on Saline Soil

Rising soil salinity has been a major problem in the soils of Egypt in recent decades. Potassium fertilization and salicylic acid (SA) play an important role in promoting plants to tolerate salt stress and increased the yield of sugar beet crop. A field experiment on sugar beet (Beta vulgaris L.) grown on saline soil was carried out during 2014 growing season in Port Said Governorate, Egypt, to study the effect of potassium fertilization of the soil at applications of 0, 100, 150, and 200 kg potassium (K) ha^?1 and foliar spray of SA by solution of 1000 mg L^?1, twice (1200 L ha^?1 each time) on yield and nutrient uptake. Application of 200 kg K ha^?1 in combination with salicylic foliar spray gave the highest root length, root diameter, shoot and root yield, sucrose, juice purity percentage, gross sugar yield, and white possible extractable sugar, nitrogen (N), phosphorus (P), and potassium (K) content, and uptake of sugar beet. The highest increase in sucrose (20%) as well as white possible extractable sugar (184%) was obtained by 200 kg K ha^?1 in combination with salicylic foliar spray compared with untreated soil with potassium fertilization and without salicylic foliar spray.     

施氮量对菊芋块茎产量、品质与植株生理特性的影响

[目的]氮肥不合理施用在导致资源浪费和环境问题的同时,还会影响菊芋正常生长发育和产量形成.研究施氮量对成熟期菊芋块茎产量、品质和生育期生理特性影响,确定关键营养指标,为菊芋高产高效施用氮肥提供理论支撑.[方法]菊芋氮肥梯度田间试验于2019年在河南省新乡市原阳县、2020年在南阳市方城县开展,2019年设N?0、60、...     

Relationship of soil properties to pyroxasulfone bioactivity in a range of prairie soils

The relationship between pyroxasulfone bioactivity and soil properties has not been investigated in a wide range of soils typical of western Canada. In this study, 47 soils from Saskatchewan, Manitoba and Alberta, with varying organic matter content (1.5%–22.1%), pH (5.0–7.9), and clay content (6.8%–59.4%) were used to evaluate the effect of soil properties on pyroxasulfone bioactivity and its relevance to field application rates. Bioactivity was assessed by measuring the reduction of sugar beet shoot length after 7 days in response to 0, 92, 184, and 368 µg?ai?kg^?1 pyroxasulfone concentration in soil. Multiple regression analysis showed that pyroxasulfone bioactivity was related to soil organic matter content, pH and clay content. Grouping the soils according to these properties allowed for a summarization of pyroxasulfone field application rates required to achieve bioactivity based on the magnitude of sugar beet shoot length inhibition (%). The estimated field application rates ranged from less than 120–480 g?ai?ha^?1.     

不同光强下红蓝光配比对樱桃萝卜生长与产量的影响

采用LED光源在室内可控环境下设置3种光照强度（180、240、300μmol·m^-2·s^-1）和2种红蓝光配比（1R:1B、2R:1B）,以研究不同光强和红蓝光配比组合对樱桃萝卜真叶数、叶绿素含量、肉质根形态以及干鲜重的影响。结果表明,光强为180μmol·m^-2·s-1时,2R:1B处理的新叶叶绿素含量略高于1R:1B处理,但地上部鲜重却略低于1R:1B处理,其它生长指标不同光质处理间无显著差异。光强为240μmol·m^-2·s^-1时,相比1R:1B 处理,2R:1B处理显著提高了樱桃萝卜的新叶叶绿素含量、地上部干鲜重、根直径、根体积、肉质根干鲜重以及干鲜根冠比（P＜0.05）。光强300μmol·m^-2·s^-1时,2R:1B处理的新叶叶绿素含量略低于1R:1B处理,但地上部干鲜重显著高于1R:1B处理（P＜0.05）,其它指标无显著差异。相同红蓝光配比下,樱桃萝卜新叶叶绿素含量、根直径、根体积、肉质根干鲜重及根冠比均随着光强的增加而增加。地上部干鲜重随光强增加的变化因光质而异。总之,一定强度的LED红蓝光质是植物工厂樱桃萝卜高产的光环境基础,并且光强高于一定水平时适宜的红蓝光配比对其生长具有显著促进作用。     

Evaluation of four different crops’ sensitivity to sulfosulfuron and tribenuron methyl soil residues

ABSTRACT

On the basis of greenhouse bioassays, the sensitivities of root and shoot biomass of barley (Hordeum vulgare L.), corn (Zea mays L.), oilseed rape (Brassica napus L.) and sugar beet (Beta vulgaris L.) to soil-incorporated sulfosulfuron and tribenuron methyl were assessed. Shoot and root biomass production was measured 30 days after emergence. Plant responses, including roots and shoots dry weight per pot, were described by a three parameter log-logistic regression model as a function of sulfosulfuron or tribenuron methyl doses and the relative sensitivities were calculated at the various ED-levels with their associated 95% confidence intervals. The most precise ED-levels were that at ED₅₀ and sensitivity rank was oilseed rape, sugar beet, corn and barley, whatever the chosen response level and herbicide. We calculated relative sensitivities at ED₁₀, ED₅₀ and ED₉₀ for the species of barley, the most tolerant crop, as reference. Comparison of relative sensitivity of crops to both herbicides showed that the sensitivity of these crops was much larger for tribenuron methyl than for sulfosulfuron. Oilseed rape was the most sensitive species (ED₅₀?=?0.202 and 0.179?µg?kg^?1 soil for root dry weight (RDW) response to sulfosulfuron and tribenuron methyl, respectively) while barley was the most tolerant one (ED₅₀?=?1.008 and 3.68?µg?kg^?1soil for RDW response to sulfosulfuron and tribenuron methyl, respectively). Sugar beet and corn had intermediate sensitivity. Also, we demonstrated how important it is to show the confidence intervals of relative sensitivities. In several instances the relative sensitivities, even numerically large, were not significantly different from 1.00. We demonstrate that classifying biotypes as resistant to a herbicide requires the threshold of resistance/susceptible (R/S) of 4.00 only be accepted if confidence intervals do not cover 1.00.