Lodging Events Research Articles

Spatial-temporal distribution and hazard assessment of maize lodging in a synergistic disaster environment

Maize, a major food crop, holds significant edible and industrial value. Lodging poses a threat to maize yields, often resulting in reduced or even zero grain production due to the prevailing growth conditions. The precise evaluation of contributing factors on maize lodging, such as adverse environmental conditions, remains limited.This study employs the M-K test, Geodetector analysis, and Receiver Operator Characteristic (ROC) curve to examine the spatial-temporal distribution of maize lodging incidents and establishes a comprehensive assessment model for spring maize lodging hazard evaluation, considering environmental variables. The findings reveal the following: (1) High wind-type lodging events (≥ 10.8 m/s by universal definition, ≥ 10 m/s in this study) occurred frequently from the jointing-tasseling stage. Wind and rain-type lodging events occurred more frequently from the milk to maturity stages compared to other phases. (2) Maize lodging hazard during the jointing stage is prominent in western Jilin province and tends to expand towards central Jilin province as the growth stages progress. (3) Topographical, soil, and climatic factors all exhibited explanatory power regarding lodging incidents, with climatic factors demonstrating a substantial contribution when combined with the other two variables. (4) The accuracy test of the ROC curve for the comprehensive model surpasses the 0.05 significant confidence threshold, indicating a strong fit. The model developed in this study enables the evaluation of maize lodging hazards during the late growth stage, enhancing the reliability of lodging disaster risk assessments.

Quantification of root lodging damage in corn using uncrewed aerial vehicle imagery

AbstractAccurate quantification of damage associated with root lodging events can help producers assess damage, predict potential yield losses, and help understand potential issues with grain quality that may arise post‐harvest (i.e., kernel weight reductions, premature germination on the ear, or vivipary). The objective of this research was to utilize imagery from an uncrewed aerial vehicle (UAV) to accurately quantify crop canopy height, grain yield, and identify trends in imagery data associated with grain quality after root lodging was imposed at multiple growth stages. Simulated corn (Zea mays L.) root lodging experiments were conducted in 2018 and 2019 with lodging treatments applied at two vegetative or two reproductive growth stages (V10, V14, VT/R1, and R3). At dough stage (R4), visible‐color and multispectral images were collected from each trial. Bare fields were also flown in February to obtain baseline elevation data. Imagery data were used to develop digital surface model (DSM) images and used to calculate indices of normalized difference red edge (NDRE) and normalized difference vegetation index (NDVI). Individual datapoints within each experimental plot were extracted from the imagery files and were compared to ground‐truth measurements. The DSM height values were similar to actual measured heights for most lodging treatments (Adj. R2 = .957). Both NDRE and NDVI exhibited linear trends with height and quality parameters (Adj. R2 = .25–.54), though yield patterns were best described using a quadratic model (Adj. R2 = .42–.60). These procedures hold utility in accurately quantifying canopy height following a root lodging event and hold promise in helping consultants identify yield and grain quality reductions associated with root lodging.

Evaluation of root lodging resistance during whole growth stage at the plant level in maize

Root lodging due to strong storm wind is a common problem in maize (Zea mays) production, leading to reduced crop yield and quality and harvest efficiency. Little information is available on quantifying effects of vertical leaf area distribution on root lodging in crops such as maize. Anti-lodging index of root was computed by the formula: ALroot = Mroot / Mwind, where AL denotes anti-lodging index, and M moment of force. Mroot, root failure moment of force equals to moment arm times max root side-pulling force measured in situ by means of the digital pole dynamometer, and Mwind, wind resultant moment of force is estimated with vertical leaf area distribution and wind speed. Two maize cultivars were examined at 5 different growth stages from V8 to physiological maturity in 2019 and 2020, in Qingdao, China. Root anti-lodging index in tested cultivars fluctuated to a small extent within any year during whole growth period excluding at V8, while there was an inter-annual shift in index means (1.23 vs 0.84). Both root failure moment and wind resultant moment increased first and then decreased with the growth stage, and their influences on root anti-lodging index varied with the year. At wind grade 6, effect sizes, as contribution to root anti-lodging index, of root moment and wind moment were respectively 0.88 and 0.98. The difference in anti-lodging index between cultivars seemed to be disappearing as wind grade goes up. Root failure moment of force positively related to single root tensile resistance, root-soil ball volume, root number and total root length, whose correlation coefficient was the maximum of 0.94. Root anti-lodging index of maize proved stable from V8 on during whole growth period, and vertical leaf area distribution played a substantial role in maize root lodging in terms of wind resultant moment. Our findings provide the insights into root lodging events in crops such as maize, and would serve an approach to assessing crop root lodging resistance in breeding and cultivation programs.

A Simple and Robust Spectral Index for Identifying Lodged Maize Using Gaofen1 Satellite Data.

Crop lodging is a major destructive factor for agricultural production. Developing a cost-efficient and accurate method to assess crop lodging is crucial for informing crop management decisions and reducing lodging losses. Satellite remote sensing can provide continuous data on a large scale; however, its utility in detecting lodging crops is limited due to the complexity of lodging events and the unavailability of high spatial and temporal resolution data. Gaofen1 satellite was launched in 2013. The short revisit cycle and wide orbit coverage of the Gaofen1 satellite make it suitable for lodging identification. However, few studies have explored lodging detection using Gaofen1 data, and the operational application of existing approaches over large spatial extents seems to be unrealistic. In this paper, we discuss the identification method of lodged maize and explore the potential of using Gaofen1 data. An analysis of the spectral features after maize lodging revealed that reflectance increased significantly in all bands, compared to non-lodged maize. A spectral sum index was proposed to distinguish lodged and non-lodged maize. Two study areas were considered: Zhaodong City in Heilongjiang Province and Ningjiang District in Jilin Province. The results of the identified lodged maize from the Gaofen1 data were validated based on three methods: first, ground sample points exhibited the overall accuracies of 92.86% and 88.24% for Zhaodong City and Ningjiang District, respectively; second, the cross-comparison differences of 1.01% for Zhaodong City and 1.13% for Ningjiang District were obtained, compared to the results acquired from the finer-resolution Planet data; and third, the identified results from Gaofen1 data and those from farmer survey questionnaires were found to be consistent. The validation results indicate that the proposed index is promising, and the Gaofen1 data have the potential for rapid lodging monitoring.

The Overlooked Biomechanical Role of the Clasping Leaf Sheath in Wheat Stalk Lodging.

The biomechanical role of the clasping leaf sheath in stalk lodging events has been historically understudied. Results from this study indicate that in some instances the leaf sheath plays an even larger role in reinforcing wheat against stalk lodging than the stem itself. Interestingly, it appears the leaf sheath does not resist bending loads by merely adding more material to the stalk (i.e., increasing the effective diameter). The radial preload of the leaf sheath on the stem, the friction between the sheath and the stem and several other complex biomechanical factors may contribute to increasing the stalk bending strength and stalk flexural rigidity of wheat. Results demonstrated that removal of the leaf sheath induces alternate failure patterns in wheat stalks. In summary the biomechanical role of the leaf sheath is complex and has yet to be fully elucidated. Many future studies are needed to develop high throughput phenotyping methodologies and to determine the genetic underpinnings of the clasping leaf sheath and its relation to stalk lodging resistance. Research in this area is expected to improve the lodging resistance of wheat.

Economic optimum plant density of sweet corn does not increase root lodging incidence

AbstractExploitation of plant density tolerance in sweet corn (Zea mays L.), including the use of density‐tolerant hybrids at plant densities that optimize economic returns (hereafter called economic optimum plant density), has the potential to improve profitability. Multiple experimental approaches, including artificially created root lodging events in field trials and natural root lodging events in growers’ fields, were used to determine if economic optimum plant densities, compared with current plant densities, increase incidence of root lodging in sweet corn. An artificially created root lodging experiment over multiple years showed the environment in which sweet corn is grown is far more important to the effects of root lodging than plant density. In trials with natural root lodging events, results showed commercial sweet corn hybrids differed greatly in their susceptibility to root lodging, with some cultivars tolerant across all plant densities. Across 16 experimental comparisons of sweet corn response to plant density where natural root lodging was observed, including seven environments and 11 commercial hybrids, there was no difference in root lodging between current and economic optimum plant densities. Factors other than plant density dominate the crop's potential for, and recovery from, root lodging in growers’ fields, namely, the hybrid and the environment in which the crop is grown.

Optimizing phenotyping methods to evaluate lodging risk for wheat

• Screening lodging traits for lodging resistance is key for wheat improvement. • Screening seven plants per plot is enough to find genetic variation for lodging traits. • Four key lodging traits can be measured to estimate lodging performance in wheat. Lodging is a complex phenomenon affecting wheat production worldwide and is a consequence of the interaction of wheat plants with abiotic (wind, rain, etc.) and biotic (e. g. plant disease, etc.) factors. Wheat breeders rely heavily on incidences of natural lodging to select lines with resistance; however, the intermittent nature of lodging events means this approach is unreliable. A model of the lodging process has been published to estimate the lodging susceptibility of plants that uses information from 15 stem and root characteristics of field grown plants that influence lodging. This approach estimates lodging susceptibility in the absence of natural lodging. However, the main shortcoming of this methodology for plant breeders is the amount of time required to measure these traits (100–150 min per plot). This study investigated two strategies to optimise the methods of estimating lodging risk in the absence of natural lodging: i) determining the minimum number of plants that must be measured per experimental plot (sample size) to identify genetic differences and ii) minimizing the number of traits required to assess lodging susceptibility increasing the feasibility to apply the methodology in a breeding context. Spring wheat grown under North West Mexico environmental conditions was established during four crop seasons (2010−11, 2011−12, 2012−13 and 2013−14) for this study. Results indicated an optimum sample size of seven plants per plot as the minimum required to identify genetic differences between cultivars with good statistical power and precision (assuming each treatment plot was replicated 3 times). Cultivar ranking and absolute values for trait dimensions were maintained when compared with larger sample sizes. A reduced number of traits can be used to estimate cultivar lodging susceptibility performances and key traits include: plant height, ear number per plant, ear area, natural frequency, breaking strength, length, diameter and wall width of one basal internode, structural rooting depth and root plate spread. Targeting these key traits, this study established that on a daily basis, 10 (47 min per plot) plots can be assessed by measuring seven plants per plot per person. Moreover, if the screening focuses only on the key traits for leverage/stem/root dimensions, then the daily plot assessment capacity would increase to 25.

Cultivar × Management Interaction to Reduce Lodging and Improve Grain Yield of Irrigated Spring Wheat: Optimising Plant Growth Regulator Use, N Application Timing, Row Spacing and Sowing Date.

Severe lodging of irrigated spring-wheat in sub-tropical Australia has previously caused yield loss of between 1.7 and 4.6 t ha–1 (20–60% of potential yield). In response, agronomic management options were assessed for their ability to reduce lodging and increase grain yield, namely plant growth regulators (PGRs), timing of nitrogen (N) application, row spacing and sowing date, in combination with long and short duration cultivars across 15 irrigated environments from 2012 to 2016. Our study identified significant interaction between genotype, environment and agronomic management (G × E × M) for grain yield and lodging, although some combinations of agronomic techniques were broadly applicable across cultivars. PGR application improved grain yield of most cultivars in well-irrigated fields that had more than 120 kg ha–1 N (mineral N + fertiliser N) at sowing, with yield gains of up to 0.5 t ha–1 observed in both lodged and non-lodged fields. However, PGRs had little effect on grain yield when soil + fertiliser N at sowing was less than 80 kg ha–1 N. In-crop N application (compared to sowing N application) often improved grain yield of short duration, lodging resistant cultivars, but reduced the yield of long-duration, lodging susceptible cultivars in some environments. Narrow row spacing of 19 cm had the highest grain yield across cultivars in low lodging environments. At a severely lodged environment, narrow rows were the highest yielding for five out of six cultivars when PGRs were used, but was the highest yielding for only half of the tested cultivars when PGRs were not used. Cultivar × sowing date interaction for grain yield was also associated with the occurrence of lodging. Neither early nor late sowing had a consistent yield benefit across a range of cultivars, as lodging severity varied between sowing date depending on the timing of storm-induced lodging events. Lodging resistant long-duration cultivars had more stable grain yield across environments and increased grain yield in response to early sowing. Further research is needed to determine the optimum management strategy for new cultivars, because farmers do not always choose the most lodging resistant cultivars for reasons of cultivar disease resistance, grain quality and seed availability.

Stalk Bending Strength is Strongly Associated with Maize Stalk Lodging Incidence Across Multiple Environments

Stalk lodging in maize results in substantial yield losses worldwide. These losses could be prevented through genetic improvement. However, breeding efforts and genetics studies are hindered by lack of a robust and economical phenotyping method for assessing stalk lodging resistance. A field-based phenotyping platform that induces failure patterns consistent with natural stalk lodging events and measures stalk bending strength in field-grown plants was recently developed. Here we examine the association between data gathered from this new phenotyping platform with counts of stalk lodging incidence on 47 maize hybrids representing a subset of genetic diversity. For comparative purposes, we examine four additional predictive phenotypes commonly assumed to be related to stalk lodging resistance; namely, rind penetrometer resistance (a.k.a. rind puncture resistance), cellulose, hemicellulose, and lignin. Lodging incidence data were gathered on 47 hybrids, grown in 98 distinct environments, spanning four years and 41 unique geographical locations in North America. Using Bayesian generalized linear mixed effects models, we show that stalk lodging incidence is associated with each of the five predictive phenotypes. Further, based on a joint analysis we demonstrate that, among the phenotypes considered, stalk bending strength measured by the new phenotyping platform is the strongest predictive phenotype of naturally occurring stalk lodging incidence in maize, followed by rind penetrometer resistance and cellulose content. This study demonstrates that field-based measurements of stalk bending strength provide a reliable estimate of stalk lodging incidence. The stalk bending strength data acquired from the new phenotyping platform will be valuable for phenotypic selection in breeding programs and for generating mechanistic insights into the genetic regulation of stalk lodging resistance.

DARLING: a device for assessing resistance to lodging in grain crops

BackgroundStalk lodging (breakage of plant stems prior to harvest) is a major problem for both farmers and plant breeders. A limiting factor in addressing this problem is the lack of a reliable method for phenotyping stalk strength. Previous methods of phenotyping stalk strength induce failure patterns different from those observed in natural lodging events. This paper describes a new device for field-based phenotyping of stalk strength called “DARLING” (device for assessing resistance to lodging in grains). The DARLING apparatus consists of a vertical arm which is connected to a horizontal footplate by a hinge. The operator places the device next to a stalk, aligns the stalk with a force sensor, steps on the footplate, and then pushes the vertical arm forward until the stalk breaks. Force and rotation are continuously recorded during the test and these quantities are used to calculate two quantities: stalk flexural stiffness and stalk bending strength.ResultsField testing of DARLING was performed at multiple sites. Validation was based upon several factors. First, the device induces the characteristic “crease” or Brazier buckling failure patterns observed in naturally lodged stalks. Second, in agreement with prior research, flexural rigidity values attained using the DARLING apparatus are strongly correlated with bending strength measurements. Third, flexural stiffness and bending strength values obtained with DARLING are in agreement with laboratory-based stiffness and strength values for corn stalks. Finally, a paired specimen experimental design was used to determine that the flexural data obtained with DARLING is in agreement with laboratory-based flexural testing results of the same specimens. DARLING was also deployed in the field to assess phenotyping throughput (# of stalks phenotyped per hour). Over approximately 5000 tests, the average testing rate was found to be 210 stalks/h.ConclusionsThe DARLING apparatus provides a quantitative assessment of stalk strength in a field setting. It induces the same failure patterns observed in natural lodging events. DARLING can also be used to perform non-destructive flexural tests. This technology has many applications, including breeding, genetic studies on stalk strength, longitudinal studies of stalk flexural stiffness, and risk assessment of lodging propensity.

QUANTIFYING LODGING PERCENTAGE, LODGING DEVELOPMENT AND LODGING SEVERITY USING A UAV-BASED CANOPY HEIGHT MODEL

Abstract. Unmanned Aerial Vehicles (UAVs) are increasingly used, and open new opportunities, in agriculture and phenotyping because of the flexible data acquisition. In this study the potential of ultra-high spatially resolved UAV image data was investigated to quantify lodging percentage, lodging development and lodging severity of barley using Structure from Motion techniques. The term lodging is defined as the permanent displacement of a plant from the upright position. Traditionally lodging quantification is based on observations that need, and vary with observers in the field. An objective threshold approach was proposed in this study to improve the accuracy in lodging determination. Across breeding trials, manual reference measurements and UAV based lodging percentage showed a very high correlation (R2 = 0.96). In addition, the multi-temporal lodging percentage development was used to estimate the recovery rate and to determine the influence of different lodging events. Based on the parameter lodging percentage an approach was developed that allowed the assessment of lodging severity, an information that is important to estimate the yield impairment. Lodging severity can be used for insurance applications, precision farming and breeder research. This trait, together with differentiated recovery are novel traits next to lodging severity that will aid the selection for genetic lines.

Remote sensing-based crop lodging assessment: Current status and perspectives

Rapid and quantitative assessment of crop lodging is important for understanding the causes of the phenomena, improving crop management, making better production and supporting loss estimates in general. Accurate information on the location and timing of crop lodging is valuable for farmers, agronomists, insurance loss adjusters, and policymakers. Lodging studies can be performed to assess the impact of lodging events or to model the risk of occurrence, both of which rely on information that can be acquired by field observations, from meteorological data and from remote sensing (RS). While studies applying RS data to assess crop lodging dates back three decades, there has been no comprehensive review of the status, potential, current approaches, and challenges in this domain. In this position paper, we review the trends in field/lab-based and RS-based studies for crop lodging assessment and discuss the strengths and weaknesses of current approaches. Theoretical background on crop lodging is presented, and the scope of RS in assessing plant characteristics associated with lodging is reviewed and discussed. The review focuses on RS-based studies, grouping them according to the platform deployed (i.e., ground-based, airborne and spaceborne), with an emphasis on analyzing the pros and cons of the technology. Finally, the challenges, research gaps, perspectives for future research, and an outlook on new sensors and platforms are presented to provide state-of-the-art and future scenarios of RS in lodging assessment. Our review reveals that the use of RS techniques in crop lodging assessment is still in an experimental stage. However, there is increasing interest within the RS scientific community (based on the increased rate of publications over time) to investigate its use for crop lodging detection and risk mapping. The existing satellite-based lodging assessment studies are very few, and the operational application of the current approaches over large spatial extents seems to be the biggest challenge. We identify opportunities for future studies that can develop quantitative models for estimating lodging severity and mapping lodging risk using RS data.

Quantifying Lodging Percentage and Lodging Severity Using a UAV-Based Canopy Height Model Combined with an Objective Threshold Approach

Unmanned aerial vehicles (UAVs) open new opportunities in precision agriculture and phenotyping because of their flexibility and low cost. In this study, the potential of UAV imagery was evaluated to quantify lodging percentage and lodging severity of barley using structure from motion (SfM) techniques. Traditionally, lodging quantification is based on time-consuming manual field observations. Our UAV-based approach makes use of a quantitative threshold to determine lodging percentage in a first step. The derived lodging estimates showed a very high correlation to reference data (R2 = 0.96, root mean square error (RMSE) = 7.66%) when applied to breeding trials, which could also be confirmed under realistic farming conditions. As a second step, an approach was developed that allows the assessment of lodging severity, information that is important to estimate yield impairment, which also takes the intensity of lodging events into account. Both parameters were tested on three ground sample distances. The lowest spatial resolution acquired from the highest flight altitude (100 m) still led to high accuracy, which increases the practicability of the method for large areas. Our new lodging assessment procedure can be used for insurance applications, precision farming, and selecting for genetic lines with greater lodging resistance in breeding research.

Monitoring crop phenology using a smartphone based near-surface remote sensing approach

Smallholder farmers play a critical role in supporting food security in developing countries. Monitoring crop phenology and disturbances to crop growth is critical in strengthening farmers’ ability to manage production risks. This study assesses the feasibility of using crowdsourced near-surface remote sensing imagery to monitor winter wheat phenology and identify damage events in northwest India. In particular, we demonstrate how streams of pictures of individual smallholder fields, taken using inexpensive smartphones, can be used to quantify important phenological stages in agricultural crops, specifically the wheat heading phase and how it can be used to detect lodging events, a major cause of crop damage globally. Near-surface remote sensing offers granular visual field data, providing detailed information on the timing of key developmental phases of winter wheat and crop growth disturbances that are not registered by common satellite remote sensing vegetation indices or national crop cut surveys. This illustrates the potential of near-surface remote sensing as a scalable platform for collecting high-resolution plot-specific data that can be used in supporting crop modeling, extension and insurance schemes to increase resilience to production risk and enhance food security in smallholder agricultural systems.

A biomechanical model for maize root lodging

Root lodging is a structural failure of the root-soil anchorage system in a plant that adversely affects its yield. It is a complex phenomenon that depends strongly on both crop genetics and environmental factors. An accurate biomechanical model to predict root lodging would disentangle the component factors and improve development of lodging resistant plants, thereby reducing the constraint of root lodging on crop yields. We developed a biomechanical model that employs an engineering safety factor approach to quantify root lodging resistance as the ratio of anchorage supply and wind demand. We also conducted field experiments to parametrize the model for a sensitivity analysis and validate the model for predictive accuracy. The sensitivity analysis revealed primary, secondary, and tertiary factors for root lodging. The primary factors consisted of root angle, structural rooting depth, soil strength, and wind speed. The secondary factors were plant height, ear height, leaf area, stalk taper, ear mass, and leaf drag. Tertiary factors were stalk diameter and leaf number. The validation analysis found the model predictions compared well with data collected from three natural lodging events, with a goodness-of-fit of 0.58. The model effectively described a collection of natural lodging events, giving confidence in its predictive accuracy as well as the relative phenotypic and envirotypic influence factors determined in the sensitivity analysis. There are significant opportunities for model improvement, perhaps most significantly in the phenomenological understanding of the physical process.

Negative effects of lodging on irrigated sugarcane productivity—An experimental and crop modelling assessment

Lodging lowers the productivity of sugarcane through a reduction in radiation use efficiency and stalk damage. However, there are few reports of experiments specifically designed to quantify effects of lodging in sugarcane. Efforts to model onset and progression of lodging, and the impact on crop productivity, have not been attempted. The objectives of this paper were to quantify effects of lodging on sugarcane and to develop modeling capability in terms of predicting lodging onset, progression and impact. Field experiments with irrigated ratoon crops were conducted at Pongola, South Africa. In one treatment the cane in each plot was allowed to grow through bamboo frames that prevented lodging. In the other treatment, the cane was not supported and could lodge at any stage. The degree of lodging was captured weekly by a rating that ranged from 1 to 9, where 1=fully erect cane and 9=completely lodged cane. At harvest estimated recoverable crystal percent (ERC %) of stalks and yield (cane and ERC) was measured for each plot. Lodging resulted in decreased ERC yields of up to 20.6%. An algorithm for simulating lodging when aboveground biomass (including rainfall and irrigation water retained on it) exceeds a variety-specific threshold, and which also considers wind speed and soil water content, was evaluated for predicting the extent and impact of lodging in the Pongola experiments, as well as for four deficit irrigation treatments of a field experiment conducted in Komatipoort, South Africa. The study showed that the onset of lodging was simulated reasonably well for various soil/crop/atmospheric conditions, while the extent of lodging at harvest was simulated very accurately for all crops. Simulated lodging was primarily driven by crop size and lodging events were triggered by rainfall that added weight to the aerial mass of the crop, and reduced the anchoring ability of the soil through saturation of the top soil. More accurate simulation of lodging, and its impacts on yield, will improve the accuracy of yield predictions by crop models, increasing their value in applications such as crop forecasting, climate change studies and exploring crop improvement and management options.

Stem lodging in sunflower: Variations in stem failure moment of force and structure across crop population densities and post-anthesis developmental stages in two genotypes of contrasting susceptibility to lodging

Stem lodging is a risk to sunflower production in Argentina, and may contribute to fixing the upper limit to commercially viable crop population density, since yield is known to increase up to densities higher than those currently used. Reputedly, crops are particularly susceptible to stem lodging during grain filling and at harvest maturity, but the temporal and spatial unpredictability of lodging events under field conditions has hampered systematic research on this issue. In this study we used mechanical lodging to examine the relationships between stem failure moment of force and stem structure in plants of two sunflower hybrids of contrasting susceptibility to stem lodging grown at each of three crop population densities (5.6 plants m −2, 10 plants m −2 and 16 plants m −2). Measurements were performed at mid- and near-end of grain filling and at harvest maturity in crops grown in three separate seasons at two locations. Stem failure moment of force at all three developmental stages was significantly ( p < 0.05) greater in the lodging-resistant hybrid than in the lodging-susceptible hybrid used in these experiments at 5.6 plants m −2, and fell with increasing crop population density and between 90% grain filling and harvest maturity in both hybrids. At harvest maturity differences in stem failure moment of force between hybrids were significant ( p < 0.05) at all three crop population densities. Stem flexural rigidity (ability of the stem to resist bending) and stem deformation (horizontal displacement from the vertical of the stem immediately prior to breakage) exhibited responses to hybrid, crop population density and developmental stage that were broadly consistent with those of stem failure moment of force. Stem diameter at the breakage point fell with crop population density, but there was little difference between hybrids except at the harvest maturity, when the susceptible hybrid at the two highest crop population densities had smaller diameters than the resistant hybrid. Measured at the breakage point, the thickness of the epidermis plus cortex tissues (i.e., the effective thickness of the stem wall) which surround the friable stem pith fell with crop population density and between end of grain filling and harvest maturity in both hybrids. Differences in effective thickness of the stem wall between hybrids were small and often not significant, but there was a tendency for the susceptible hybrid to exhibit greater thickness of the effective stem wall, particularly at the two higher population densities. Stem failure moment of force was linearly related to thickness of the effective stem wall in both hybrids, the slope of the relationship being significantly greater for the resistant hybrid. We conclude that, within limits, the thickness of the effective stem wall may prove to be useful as a guide to genotype susceptibility to stem lodging in breeding programs and may offer a simple approach to modelling susceptibility. This work has also served to highlight the need to investigate the origins (presumably related to stem anatomy and/or cell wall properties) of the genotypic effects on the stem failure moment of force/the effective stem wall relationship. Finally, the demonstration of the existence of genotype differences in tolerance to stem lodging should encourage the execution of a broader survey aimed at identifying sources of tolerance to stem lodging at high crop population densities in sunflower.

Screening for lodging resistance in spring wheat breeding programmes

AbstractSelection for lodging resistance in Canadian hard red spring wheat under natural conditions is difficult due to the sporadic and often random nature of lodging events. We conducted field trials in Edmonton AB Canada (2000–2002) to determine if either a high seeding rate, or artificially inducing lodging (by dragging a weighted apparatus across plots at the early milk stage), would be an effective screen for determining genetic lodging resistance in wheat breeding programmes. For the 25 genotypes tested, applying artificial lodging at the experimental mean early milk stage was a suitable method to screen and identify lodging tolerant and susceptible genotypes. Tolerance to artificially induced lodging was mainly found within semi‐dwarf genotypes, and susceptibility was mainly found within Canadian bread wheat genotypes. Severe lodging resulted in yield losses as high as 40%. Lodging tolerant genotypes identified in this study are now being crossed into elite western Canadian bread wheat in an effort to increase genetic lodging resistance within Canadian breeding lines.

Methods for Rapidly Measuring the Lodging Resistance of Wheat Cultivars

AbstractLodging resistance ratings for winter wheat cultivars are frequently based upon observations of lodging. This is an unreliable method because of the frequent occurrence of years without significant lodging events. It also does not distinguish between stem and root lodging resistance. This paper describes the development and testing of instrumentation and procedures for two field‐based methods to rapidly assess stem and root lodging resistance. Both methods used a specifically designed instrument for measuring the resistance of shoots against rotational displacement. Stem lodging resistance was assessed when the soil was dry and strong, whereas resistance to root lodging was assessed after the soil had been weakened by irrigation. Tests were carried out on 14 winter wheat cultivars grown at two sites in the UK during 2002. Both methods were able to detect statistically significant differences between the cultivars for their resistance to stem and root lodging. A comparison of these results with observations of lodging in the field showed that the methods accounted for about 60 and 50 % of the stem and root lodging respectively.