Evaluation of Root Lodging Resistance During Whole Growth Period in Maize Using the Anti-Lodging Index Defined as Root Failure Moment Divided by Wind Resultant Moment

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. The anti-lodging index of root was computed by the formula: ALroot = Mroot / Mwind, where AL denotes anti-lodging index, and M moment of force. 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 wind resultant moment of force is estimated with vertical leaf area distribution and wind speed. Two maize cultivars, with contrasting root lodging resistance, 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 influence 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.

Evaluation of root lodging resistance during whole growth period in maize using the anti-lodging index defined as root failure moment divided by wind resultant moment

Background: 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. The anti-lodging index of root was computed by the formula: ALroot = Mroot / Mwind, where AL denotes anti-lodging index, and M moment of force. 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 wind resultant moment of force is estimated with vertical leaf area distribution and wind speed. Two maize cultivars, with contrasting root lodging resistance, were examined at 5 different growth stages from V8 to physiological maturity in 2019 and 2020, in Qingdao, China. Results: 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 influence 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. Conclusion: 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 new empirical equation to describe the vertical leaf distribution profile of maize

The characteristic traits of maize (Zea mays L.) leaves affect light interception and photosynthesis. Measurement or estimation of individual leaf area has been described using discontinuous equations or bell-shaped functions. However, new maize hybrids show different canopy architecture, such as leaf angle in modern maize which is more upright and ear leaf and adjacent leaves which are longer than older hybrids. The original equations and their parameters, which have been used for older maize hybrids and grown at low plant densities, will not accurately represent modern hybrids. Therefore, the aim of this paper was to develop a new empirical equation that captures vertical leaf distribution. To characterize the vertical leaf profile, we conducted a field experiment in Jilin province, Northeast China from 2015 to 2018. Our new equation for the vertical distribution of leaf profile describes leaf length, width or leaf area as a function of leaf rank, using parameters for the maximum value for leaf length, width or area, the leaf rank at which the maximum value is obtained, and the width of the curve. It thus involves one parameter less than the previously used equations. By analysing the characteristics of this new equation, we identified four key leaf ranks (4, 8, 14 and 20) for which leaf parameter values need to be quantified in order to have a good estimation of leaf length, width and area. Together, the method of leaf area estimation proposed here adds versatility for use in modern maize hybrids and simplifies the field measurements by using the four key leaf ranks to estimate vertical leaf distribution in maize canopy instead of all leaf ranks.

A Multi-Layer Model for Transpiration of Urban Trees Considering Vertical Structure

As the intensity of the urban heat island effect increases, the cooling effect of urban trees has become important. Urban trees cool surfaces during the day via shading, increasing albedo and transpiration. Many studies are being conducted to calculate the transpiration rate; however, most approaches are not suitable for urban trees and oversimplify plant physiological processes. We propose a multi-layer model for the transpiration of urban trees, accounting for plant physiological processes and considering the vertical structure of trees and buildings. It has been expanded from an urban canopy model to accurately simulate the photosynthetically active radiation and leaf surface temperature. To evaluate how tree and surrounding building conditions affect transpiration, we simulated the transpiration of trees in different scenarios such as building height (i.e., 1H, 2H and 3H, H = 12 m), tree location (i.e., south tree and north tree in a E-W street), and vertical leaf area density (LAD) (i.e., constant density, high density with few layers, high density in middle layers, and high density in lower layers). The transpiration rate was estimated to be more sensitive to the building height and tree location than the LAD distribution. Transpiration-efficient trees differed depending on the surrounding condition and plant location. This model is a useful tool that provides guidelines on the planting of thermo-efficient trees depending on the structure or environment of the city.

Suitability of Airborne and Terrestrial Laser Scanning for Mapping Tree Crop Structural Metrics for Improved Orchard Management

Airborne Laser Scanning (ALS) and Terrestrial Laser Scanning (TLS) systems are useful tools for deriving horticultural tree structure estimates. However, there are limited studies to guide growers and agronomists on different applications of the two technologies for horticultural tree crops, despite the importance of measuring tree structure for pruning practices, yield forecasting, tree condition assessment, irrigation and fertilization optimization. Here, we evaluated ALS data against near coincident TLS data in avocado, macadamia and mango orchards to demonstrate and assess their accuracies and potential application for mapping crown area, fractional cover, maximum crown height, and crown volume. ALS and TLS measurements were similar for crown area, fractional cover and maximum crown height (coefficient of determination (R2) ≥ 0.94, relative root mean square error (rRMSE) ≤ 4.47%). Due to the limited ability of ALS data to measure lower branches and within crown structure, crown volume estimates from ALS and TLS data were less correlated (R2 = 0.81, rRMSE = 42.66%) with the ALS data found to consistently underestimate crown volume. To illustrate the effects of different spatial resolution, capacity and coverage of ALS and TLS data, we also calculated leaf area, leaf area density and vertical leaf area profile from the TLS data, while canopy height, tree row dimensions and tree counts) at the orchard level were calculated from ALS data. Our results showed that ALS data have the ability to accurately measure horticultural crown structural parameters, which mainly rely on top of crown information, and measurements of hedgerow width, length and tree counts at the orchard scale is also achievable. While the use of TLS data to map crown structure can only cover a limited number of trees, the assessment of all crown strata is achievable, allowing measurements of crown volume, leaf area density and vertical leaf area profile to be derived for individual trees. This study provides information for growers and horticultural industries on the capacities and achievable mapping accuracies of standard ALS data for calculating crown structural attributes of horticultural tree crops.

Remote Estimation of Nitrogen Vertical Distribution by Consideration of Maize Geometry Characteristics

The vertical leaf nitrogen (N) distribution in the crop canopy is considered to be an important adaptive response of crop growth and production. Remote sensing has been widely applied for the determination of a crop’s N status. Some studies have also focused on estimating the vertical leaf N distribution in the crop canopy, but these analyses have rarely considered the plant geometry and its influences on the remote estimation of the N vertical distribution in the crop canopy. In this study, field experiments with three types of maize (Zea mays L.) plant geometry (i.e., horizontal type, intermediate type, and upright type) were conducted to demonstrate how the maize plant geometry influences the remote estimation of N distribution in the vertical canopy (i.e., upper layer, middle layer, and bottom layer) at different growth stages. The results revealed that there were significant differences among the three maize plant geometry types in terms of canopy architecture, vertical distribution of leaf N density (LND, g m−2), and the LND estimates in the leaves of different layers based on canopy hyperspectral reflectance measurements. The upright leaf variety had the highest correlation between the lower-layer LND (R2 = 0.52) and the best simple ratio (SR) index (736, 812), and this index performed well for estimating the upper (R2 = 0.50) and middle (R2 = 0.60) layer LND. However, for the intermediate leaf variety, only 25% of the variation in the lower-layer LND was explained by the best SR index (721, 935). The horizontal leaf variety showed little spectral sensitivity to the lower-layer LND. In addition, the growth stages also affected the remote detection of the lower leaf N status of the canopy, because the canopy reflectance was dominated by the biomass before the 12th leaf stage and by the plant N after this stage. Therefore, we can conclude that a more accurate estimation of the N vertical distribution in the canopy is obtained by canopy hyperspectral reflectance when the maize plants have more upright leaves.

Estimating Changes in Leaf Area, Leaf Area Density, and Vertical Leaf Area Profile for Mango, Avocado, and Macadamia Tree Crowns Using Terrestrial Laser Scanning

Vegetation metrics, such as leaf area (LA), leaf area density (LAD), and vertical leaf area profile, are essential measures of tree-scale biophysical processes associated with photosynthetic capacity, and canopy geometry. However, there are limited published investigations of their use for horticultural tree crops. This study evaluated the ability of light detection and ranging (LiDAR) for measuring LA, LAD, and vertical leaf area profile across two mango, macadamia and avocado trees using discrete return data from a RIEGL VZ-400 Terrestrial Laser Scanning (TLS) system. These data were collected multiple times for individual trees to align with key growth stages, essential management practices, and following a severe storm. The first return of each laser pulse was extracted for each individual tree and classified as foliage or wood based on TLS point cloud geometry. LAD at a side length of 25 cm voxels, LA at the canopy level and vertical leaf area profile were calculated to analyse tree crown changes. These changes included: (1) pre-pruning vs. post-pruning for mango trees; (2) pre-pruning vs. post-pruning for macadamia trees; (3) pre-storm vs. post-storm for macadamia trees; and (4) tree leaf growth over a year for two young avocado trees. Decreases of 34.13 m2 and 8.34 m2 in LA of mango tree crowns occurred due to pruning. Pruning for the high vigour mango tree was mostly identified between 1.25 m and 3 m. Decreases of 38.03 m2 and 16.91 m2 in LA of a healthy and unhealthy macadamia tree occurred due to pruning. After flowering and spring flush of the same macadamia trees, storm effects caused a 9.65 m2 decrease in LA for the unhealthy tree, while an increase of 34.19 m2 occurred for the healthy tree. The tree height increased from 11.13 m to 11.66 m, and leaf loss was mainly observed between 1.5 m and 4.5 m for the unhealthy macadamia tree. Annual increases in LA of 82.59 m2 and 59.97 m2 were observed for two three-year-old avocado trees. Our results show that TLS is a useful tool to quantify changes in the LA, LAD, and vertical leaf area profiles of horticultural trees over time, which can be used as a general indicator of tree health, as well as assist growers with improved pruning, irrigation, and fertilisation application decisions.