Field Canopy Research Articles

Hyperspectral multivariate linear prediction model of tobacco (nicotiana tabacum L.) Leaf nitrogen content

In order to accurately and effectively obtain the nitrogen content of tobacco leaves during the whole growth period, in the present study the field canopy spectrum of the three critical periods of tobacco rosette stage, vigorous growth stage and topping stage were used. The correlation analysis of field canopy spectrum, first derivative spectrum, hyperspectral parameters and vegetation index with the nitrogen content of tobacco leaves was carried out one by one, and the prediction model was established by multiple linear regression using the variables with the best correlation coefficient. Results showed that the first derivative spectrum, EVI II and green peak position had strong correlation, which is suitable for introducing multivariate equations as independent variables. Finally, the modeling determination coefficient (R2) was 0.66, RMSE was 0.40, and MAPE was 11%. The validation results showed that R2 was 0.73, RMSE was 0.38, and MAPE was 8.33%, which proved that this model could accurately predict the nitrogen content of tobacco leaves and could meet the requirements of large-scale statistical monitoring of tobacco quality indicators in the field. Bangladesh J. Bot. 52(2): 575-584, 2023 (June) Special

Hyperspectral multivariate linear prediction model of tobacco (nicotiana tabacum L.) Leaf nitrogen content

In order to accurately and effectively obtain the nitrogen content of tobacco leaves during the whole growth period, in the present study the field canopy spectrum of the three critical periods of tobacco rosette stage, vigorous growth stage and topping stage were used. The correlation analysis of field canopy spectrum, first derivative spectrum, hyperspectral parameters and vegetation index with the nitrogen content of tobacco leaves was carried out one by one, and the prediction model was established by multiple linear regression using the variables with the best correlation coefficient. Results showed that the first derivative spectrum, EVI II and green peak position had strong correlation, which is suitable for introducing multivariate equations as independent variables. Finally, the modeling determination coefficient (R2) was 0.66, RMSE was 0.40, and MAPE was 11%. The validation results showed that R2 was 0.73, RMSE was 0.38, and MAPE was 8.33%, which proved that this model could accurately predict the nitrogen content of tobacco leaves and could meet the requirements of large-scale statistical monitoring of tobacco quality indicators in the field. Bangladesh J. Bot. 52(2): 575-584, 2023 (June) Special

Sprayer boom height measurement in wheat field using ultrasonic sensor: An exploratory study.

In order to explore the influencing factors and laws of ultrasonic sensor detecting wheat canopy height, designed an ultrasonic sensor detection height test platform with speed adjustable function. Taking step surface, bare soil and wheat canopy as the research objects, a canopy height calculation method based on K-mean clustering is proposed, and the response characteristics of ultrasonic detection to three media under different operating speeds are explored. Firstly, the step detection test results show that the average detection error of ultrasonic sensor is 1.35%. When the sensor detection distance is switched at the step, with the increase of detection distance, the actual offset at the step increases first and then tends to be stable, and the maximum offset is 10.4cm. The test results of bare soil slope show that the relative error between the detection distance and the manual measurement distance is 1.4% under quasi-static conditions. The leading or lagging of detection under moving conditions is affected by multiple factors such as terrain undulation, speed and detection range. The detection test results of wheat canopy showed that the detection distance was larger than the manual measurement distance, and the smaller the canopy density, the greater the detection error and error variance. When the moving speed is 0.3m/s-1.2m/s, the average detection deviation of the ultrasonic sensor for five kinds of wheat canopy density is 0.14m, and the maximum variance of the detection deviation is 0.07cm2. In this paper, the research on the response characteristics of ultrasonic to the detection of bare soil and sparse canopy in wheat field can provide technical support for the detection of crop canopy in the field.

Increased bundle-sheath leakiness of CO2 during photosynthetic induction shows a lack of coordination between the C4 and C3 cycles.

Use of a complete dynamic model of NADP-malic enzyme C4 photosynthesis indicated that, during transitions from dark or shade to high light, induction of the C4 pathway was more rapid than that of C3 , resulting in a predicted transient increase in bundle-sheath CO2 leakiness (ϕ). Previously, ϕ has been measured at steady state; here we developed a new method, coupling a tunable diode laser absorption spectroscope with a gas-exchange system to track ϕ in sorghum and maize through the nonsteady-state condition of photosynthetic induction. In both species, ϕ showed a transient increase to > 0.35 before declining to a steady state of 0.2 by 1500 s after illumination. Average ϕ was 60% higher than at steady state over the first 600 s of induction and 30% higher over the first 1500 s. The transient increase in ϕ, which was consistent with model prediction, indicated that capacity to assimilate CO2 into the C3 cycle in the bundle sheath failed to keep pace with the rate of dicarboxylate delivery by the C4 cycle. Because nonsteady-state light conditions are the norm in field canopies, the results suggest that ϕ in these major crops in the field is significantly higher and energy conversion efficiency lower than previous measured values under steady-state conditions.

Resistance characteristics of broad-leaf crop canopy in air-assisted spray field and their effects on droplet deposition.

Air-assisted spray technology is widely applied in high-efficiency pesticide applications. The resistance characteristics of the crop canopy reflect its energy dissipation effect on the assisted airflow, connecting the structure of the crop canopy, assisted airflow velocity, and droplet deposition effect. Using a common broad-leaf crop canopy as the research object, the resistance characteristics of the crop canopy in the air-assisted field were investigated in this study by performing theoretical analysis and wind tunnel tests. Further, the feasibility of using the resistance characteristics of the crop canopy was assessed to evaluate its droplet deposition effect. The results showed that under the conditions of different number of leaf layers and initial leaf azimuth angles, the canopy pressure drop experiences a non-linear increasing trend with increasing assisted airflow velocity and that its regression function conforms to the Darcy–Forchheimer function. Moreover, when the initial azimuth angles of single- and multi-layer leaves were 90°–270°, the change rate of the canopy pressure drop with airflow velocity was 7–9 m/s, and there was a critical wind speed. However, with an increasing number of leaf layers in the crop canopy and changes in the initial leaf azimuth angle, the corresponding changes between the maximum canopy pressure drop and resistance coefficient were non-linear. Thus, it is proposed that the resistance characteristics of multi-layer leaves cannot be quantified as the results of the linear superposition of the resistance characteristics of several single-layer leaves—that is, it should be regarded as a whole research object. Combined with the analysis of the influence of the crop canopy resistance on droplet deposition, it is considered that when the crop canopy has multiple leaf layers in the airflow direction, the existing air-assisted spray technology cannot guarantee droplet deposition and canopy penetration simultaneously.

Lolium perenne engineered for elevated leaf lipids exhibits greater energy density in field canopies under defoliation

Co-expression of diacylglycerol O -acyltransferase (DGAT1) and a lipid droplet-stabilizing protein called Cys-oleosin (collectively ‘HME’ technology) increases foliar lipid concentrations and plant biomass, which could elevate energy yields from perennial ryegrass (PR, Lolium perenne L.)-based pastures. Quantifying the feasible benefits of HME PR necessitates that herbage growth and energy density are quantified on a ground area basis under regular defoliation. We examined the translation, from spaced pots indoors to field canopies (swards), of the fatty acid (FA), gross energy (GE), and biomass enhancing traits associated with HME technology expression in PR. Under controlled indoor conditions in spaced pots, hemizygous HME seedlings with 32% higher leaf FA content (1.2%DW) than null controls exhibited a faster rate of leaf extension. These effects translated into a stable 0.2–0.5 kJ/gDW increase in herbage GE concentration, and a 6–10% herbage growth rate advantage when HME ‘miniswards’ were grown under moderate light competition (LAI 7–9) for five defoliation and regrowth cycles (harvests). However, subsequent growth in a dense canopy (LAI>10) eliminated this HME herbage growth advantage. In two field trials in the Midwest United States, hemizygous HME swards exhibited 25–34% (0.8–1%DW) higher end-of-season herbage FA content than null control swards, and 0.2–0.5 kJ/gDW higher end-of-season herbage GE. Herbage growth rates were generally similar for HME and null control swards across both field seasons. This thorough analysis of trait translation shows that the benefits of enhanced FA and GE translate to HME PR canopies grown in the field. The intrinsic growth advantage of HME PR may be diminished in field canopies such that yield benefits are realized only under limited conditions.

Characterizing Canopy Openness Across Large Forested Landscapes Using Spherical Densiometer and Smartphone Hemispherical Photography

AbstractCanopy openness is an important forest characteristic related to understory light environment and productivity. Although many methods exist to estimate canopy openness, comparisons of their performance tend to focus on relatively narrow ranges of canopy conditions and forest types. To address this gap, we compared two popular approaches for estimating canopy openness, traditional spherical densiometer and modern smartphone hemispherical photography, across a large range of canopy conditions (from closed canopy to large gaps) and forest types (from low-elevation broadleaf to high-elevation conifer forests) across four states in the northeastern United States. We took 988 field canopy openness measurements (494 per instrument) and compared them across canopy conditions using linear regression and t-tests. The extensive replication allowed us to quantify differences between the methods that may otherwise go unnoticed. Relative to the densiometer, smartphone photography overestimated low canopy openness (<10%) but it underestimated higher canopy openness (>10%), regardless of forest type.

Vertical distribution of gas exchanges and their integration throughout the entire canopy in a maize field.

Fluxes of carbon and water along a vertical profile within a canopy, particularly the associations between canopy and ecosystem levels, are not well studied. In this study, gas exchange along the vertical profile in a maize canopy was examined. The relationships between leaf- and ecosystem-level carbon and water fluxes were compared. The results from research conducted over two growing seasons showed that during vegetative growth, the top and middle leaf layers in the canopy contribute most to the carbon and water fluxes of the entire canopy. During the grain-filling stage, gasexchange processes were performed mostly in the middle leaves with and near the ears. Significant relationships were observed between the net ecosystem CO2 exchange rate (NEE) plus soil respiration and the assumed canopy levels (Acanopy) and between evapotranspiration rates at the ecosystem (ET) and assumed canopy levels (Ecanopy). This highlights the close associations between these parameters by integrating the leaf gasexchange rates measured in a conventional leaf cuvette and those at the ecosystem level via the eddy covariance technique. These results improve our understanding of how carbon assimilation varies vertically within a canopy, highlighting the critical role of ear leaves.

Assessment of oil palm yield and biophysical suitability in Indonesia and Malaysia

ABSTRACT The most crucial technical challenge facing the Malaysian and Indonesian oil palm industry is that the actual yield in the form of Fresh Fruit Bunch (FFB; unit in tonne per hectare (t ha−1)) are well below of potential levels and have stagnated over last two decades. Closing this wide yield gap would have a positive impact on the revenue as it increases productivity per hectare and it eventually leads to less pressure on opening new land and mitigates environmental costs of production. With respect to the indispensable need for closing this gap for future prosperity of this industry and sustainable production of palm oil, this study assessed oil palm yield, considering the potential growth of oil palm dependent on the site qualities and actual yield. Firstly, we mapped oil palm plantations combining yearly Advanced Land Observation Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) and ALOS-2 mosaics of L-band backscatter, Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance (MOD13Q1), and the MODIS Vegetation Continuous Field canopy cover product (MOD44B); where 10.3 and 6.68 million ha (Mha) of oil palm plantations were mapped, respectively, in Indonesia and Malaysia in 2017. Secondly, the age after planting was estimated at detected plantations using time series of MODIS canopy cover with correlation coefficient (r) of 0.68 and Root Mean Square Error (RMSE) of 4.7 years. Thirdly, the biophysical suitability of detected plantations was evaluated considering the spatial-temporal variation of different biophysical criteria. Combining information from second and third steps, we estimated the potential yield at 250 m spatial resolution. The average potential yield in Malaysia ranges between 13.8 t ha−1 and 19.3 t ha−1 in 2017, where in Indonesia it ranges between 17.8 t ha−1 and 21.7 t ha−1 in the same year. The actual yield in next step, has been quantified by HH-HV attribute of ALOS PALSAR and ALOS-2 mosaics, where the average actual yield in Malaysia ranges between 14.48 t ha−1 and 20.63 t ha−1 and in Indonesia it ranges between 8.49 t ha−1 and15.40 t ha−1 in 2017. Finally, comparing estimated potential and actual yields, we evaluated oil palm industries’ performances where distinct differences were found between two countries. In most of the Malaysian states quantified actual yields were above or at the level of estimated potential yields, whereas in all Indonesian provinces quantified actual yields were well below the potential level. Considering the favourability of environment, among all provinces/states, Sabah, and Sarawak states in Malaysia and Aceh and North Kalimantan provinces in Indonesia distinctly differ due to their poor performances from rest of provinces/states. The information on different yields provided in this study are indispensable needs for efficient and accountable policies as it enables governors to directly target specific objectives such as subsidies on fertilizers, productive cultivars, and new technologies for the plantations suffering from low yield. Also, this study provides benchmarks for each province/state for scopes of actual yield improvements for long-term planning.

Evaluation of the Simard et al. 2011 Global Canopy Height Map in Boreal Forests

Light detection and ranging (LiDAR) provides a state-of-the-art technique for measuring forest canopy height. Nevertheless, it may miss some forests due to its spatial separation of individual spots. A number of efforts have been made to overcome the limitation of global LiDAR datasets to generate wall-to-wall canopy height products, among which a global satellite product produced by Simard et al. (2011) (henceforth, the Simard-map) has been the most widely applied. However, the accuracy of the Simard-map is uncertain in boreal forests, which play important roles in the terrestrial carbon cycle and are encountering more extensive climate changes than the global average. In this letter, we evaluated the Simard-map in boreal forests through a literature review of field canopy height. Our comparison shows that the Simard-map yielded a significant correlation with the field canopy height (R2 = 0.68 and p < 0.001). However, remarkable biases were observed with the root mean square error (RMSE), regression slope, and intercept of 6.88 m, 0.448, and 10.429, respectively. Interestingly, we found that the evaluation results showed an identical trend with a validation of moderate-resolution imaging spectroradiometer (MODIS) tree-cover product (MOD44B) in boreal forests, which was used as a crucial input data set for generating the Simard-map. That is, both the Simard-map and MOD44B yielded an overestimation (underestimation) in the lower (upper) tails of the scatterplots between the field and satellite data sets. This indicates that the MOD44B product is the likely source of error for the estimation biases of the Simard-map. Finally, a field calibration was performed to improve the Simard-map in boreal forests by compensating for the estimation biases and discarding non-forest areas, which provided a more reliable canopy height product for future applications.

Impacts of different radiometric calibration methods on the retrievals of sun-induced chlorophyll fluorescence and its relation to productivity for continuous field measurements

Sun-induced chlorophyll fluorescence (SIF), now observed from space on a global scale, has been shown to be a powerful proxy for photosynthetic activity. Long-term in situ field canopy SIF measurements are improving, enabling better understanding of SIF signal and support to satellite missions. Since SIF retrievals rely on the absolute irradiance radiance measurements, accurate outdoor radiometric calibration is necessary to provide accurate radiance data, especially for long-term continuous measurements on forest stands. However, standard laboratory calibration methods are not practical to be performed for outdoor long-term measurements, and several in-field alternative methods are generally used, which may result in some uncertainties. Here we evaluate the effects of different radiometric calibration methods on SIF retrievals and its relation with gross primary productivity (GPP) at the canopy level. Three widely used methods are used, i.e., well-established laboratory methods with integrating sphere, laboratory-calibrated reference spectrometer (ASD FieldSpec Pro), and a light calibration source with a white reference panel. Our results indicate that different radiometric calibrations have marginal effects on vegetation indices but have significant effects on the SIF absolute value, and have slight effects on diurnal and seasonal patterns of SIF. Moreover, the relationships between GPP and SIF retrieved using different calibration coefficients are similar at both diurnal and seasonal scales, but with different regression slopes. Therefore, we recommend that a standard laboratory radiometric calibration is conducted using an integrating sphere before installation in the field and a regular in-field calibration with a well-calibrated spectrometer and white reference, especially for long-term observation above a forest canopy. Our findings have strong implications for the ongoing and future ground canopy SIF measurements and suggest the need for a consistent radiometric calibration method, especially for cross-site comparison studies.

Hyperspectral remote sensing to quantify the flowering phenology of winter wheat

Flowering phenology, as a sensitive bio-indicator to climate change, has been attracting increasing concern. However, less information is available so far for quantifying flowering phenological stages by use of hyperspectral remote sensing in winter wheat. The establishment of a vegetation index, which is sensitive to the changes of flowering rate, is important to allow the monitoring of flowering phenology through hyperspectral remote sensing. A field experiment was conducted at the Agro-meteorological Station, Nanjing University of Information Science and Technology, Jiangsu Province, China, with two nighttime warming levels, i.e., nighttime warming and ambient temperature (control), and two sowing levels, i.e., normal sowing and late sowing. The field canopy reflectance spectrum was synchronously determined with the flowering rate within 0.25 m2 area at the flowering stage of winter wheat. This study developed a new index for estimating the flowering rate that was compared with the published indices for estimating canopy structure parameter. The newly developed two bands-index (R446 − R472)/(R446 + R472), generated coefficients of determination, root mean square error, and residual prediction deviation values between the measured and predicted values of 0.75, 18.69%, and 1.66, respectively. The study suggests that hyperspectral remote sensing can be used to quantify flowering phenology in winter wheat.

Changes in the vertical distribution of leaf area enhanced light interception efficiency in maize over generations of selection.

Breeders select for yield, thereby indirectly selecting for traits that contribute to it. We tested if breeding has affected a range of traits involved in plant architecture and light interception, via the analysis of a panel of 60 maize hybrids released from 1950 to 2015. This was based on novel traits calculated from reconstructions derived from a phenotyping platform. The contribution of these traits to light interception was assessed in virtual field canopies composed of 3D plant reconstructions, with a model tested in a real field. Two categories of traits had different contributions to genetic progress. (a) The vertical distribution of leaf area had a high heritability and showed a marked trend over generations of selection. Leaf area tended to be located at lower positions in the canopy, thereby improving light penetration and distribution in the canopy. This potentially increased the carbon availability to ears, via the amount of light absorbed by the intermediate canopy layer. (b) Neither the horizontal distribution of leaves in the relation to plant rows nor the response of light interception to plant density showed appreciable trends with generations. Hence, among many architectural traits, the vertical distribution of leaf area was the main indirect target of selection.

Potential and Limits of Retrieving Conifer Leaf Area Index Using Smartphone-Based Method

Forest leaf area index (LAI) is a key characteristic affecting a field canopy microclimate. In addition to traditional professional measuring instruments, smartphone-based methods have been used to measure forest LAI. However, when smartphone methods were used to measure conifer forest LAI, very different performances were obtained depending on whether the smartphone was held at the zenith angle or at a 57.5° angle. To further validate the potential of smartphone sensors for measuring conifer LAI and to find the limits of this method, this paper reports the results of a comparison of two smartphone methods with an LAI-2000 instrument. It is shown that the method with the smartphone oriented vertically upwards always produced better consistency in magnitude with LAI-2000. The bias of the LAI between the smartphone method and the LAI-2000 instrument was explained with regards to four aspects that can affect LAI: gap fraction; leaf projection ratio; sensor field of view (FOV); and viewing zenith angle (VZA). It was concluded that large FOV and large VZA cause the 57.5° method to overestimate the gap fraction and hence underestimate conifer LAI. For the vertically upward method, the bias caused by the overestimated gap fraction is compensated for by an underestimated leaf projection ratio.

Remote Monitoring of Heading Rice Growing and Nitrogen Content Based on UAV Images

Rice heading is the critical stage of the growth of rice, rice plants are relatively large, field canopy, poor resistance, and coincided with the high temperature and rainy weather, pests and diseases are more prone period. Therefore, the use of UAV to monitor the growth status of rice, easy to understand rice growth and nutritional status, in order to achieve high-quality, high yield, efficient purpose. This article is the field experiments under different nitrogen levels, using UAV monitoring multispectral images of rice, by reference remote sensing spectral indices, derived green normalized difference vegetation index (GNDVI) relative to other spectral index is more suitable for rice field biomass inversion modeling. At the same time, this study is based on the inversion model, implemented the rice growing and nitrogen content graded by ISODATA methods in ENVI. Achieved classification on rice growth and nitrogen remote sensing thematic map in ArcGIS, to provide timely and accurate information for rice seedling diagnosis and management decision, has reached the purpose of rice production precise management.

Mapping spatial distribution and biomass of coastal wetland vegetation in Indonesian Papua by combining active and passive remotely sensed data

Abstract There is ongoing interest to develop remote sensing methods for mapping and monitoring the spatial distribution and biomass of mangroves. In this study, we develop a suite of methods to evaluate the combination of Landsat-8, ALOS PALSAR, and SRTM data for mapping spatial distribution of mangrove composition, canopy height, and aboveground biomass in the wide intertidal zones and coastal plains of Mimika district, Papua, Indonesia. Image segmentation followed by visual interpretation of composite PALSAR images was used to delineate mangrove areas, whereas a flexible statistical rule based classification of spectral signatures from Landsat-8 images was used to classify mangrove associations. The overall accuracy of land cover classification was 94.38% with a kappa coefficient of 0.94 when validated with field inventory data and Google Earth images. Mangrove height and aboveground biomass were mapped using the SRTM DEM, which were calibrated with field-measured data via quantile regression models. There was a strong correlation between the SRTM DEM and the 0.98 quantile of field canopy heights (H .98 ), which was used to represent the tallest trees in each of 196 10 m radius subplots (r = 0.84 and R 2 = 0.804). Model performance was evaluated through 10,000 bootstrapped simulations, producing a mean absolute error (MAE) of 3.0 m for canopy height estimation over 30 m pixels of SRTM data. Quantile regression revealed a relatively strong non-linear relationship between the SRTM derived canopy height model and aboveground biomass measured in 0.5 ha mangrove inventory plots (n = 33, R 2 = 0.46). The model results produced estimates of mean standing biomass of 237.52 ± 98.2 Mg/ha in short canopy ( Avicennia / Sonneratia ) stands to 353.52 ± 98.43 Mg/ha in mature tall canopy ( Rhizophora ) dominated forest. The model estimates of mangrove biomass were within 90% confidence intervals of area-weighted biomass derived from field measurements. When validated at the landscape scale, the difference between modeled and measured aboveground mangrove biomass was 3.48% with MAE of 105.75 Mg/ha. These results indicate that the approaches developed here are reliable for mapping and monitoring mangrove composition, height, and biomass over large areas of Indonesia.

Estimation of arsenic in agricultural soils using hyperspectral vegetation indices of rice

This study systematically analyzed the performance of multivariate hyperspectral vegetation indices of rice (Oryza sativa L.) in estimating the arsenic content in agricultural soils. Field canopy reflectance spectra was obtained in the jointing-booting growth stage of rice. Newly developed and published multivariate vegetation indices were initially calculated to estimate soil arsenic content. The well-performing vegetation indices were then selected using successive projections algorithm (SPA), and the SPA selected vegetation indices were adopted to calibrate a multiple linear regression model for estimating soil arsenic content. Results showed that a three-band vegetation index (R716−R568)/(R552−R568) performed best in the newly developed vegetation indices in estimating soil arsenic content. The photochemical reflectance index (PRI) and red edge position (REP) performed well in the published vegetation indices. Moreover, the linear combination of two vegetation indices ((R716−R568)/(R552−R568) and REP) selected using SPA improved the estimation of soil arsenic content. These results indicated that the newly developed three-band vegetation index (R716−R568)/(R552−R568) might be recommended as an indicator for estimating soil arsenic content in the study area. PRI and REP could be used as universal vegetation indices for monitoring soil arsenic contamination.

Study of evapotranspiration and evaporation beneath the canopy in a buckwheat field

The determination of evaporation and transpiration separately is very important in improving water use efficiency and developing exact irrigation scheduling. Hourly crop evapotranspiration (ET c) and soil evaporation (E g) beneath the buckwheat canopy were measured using Bowen ratio energy balance method and micro-lysimeters, respectively. The total ET c and E g in the whole growth season of buckwheat were 187.4 and 72.1 mm, respectively. Crop coefficient of buckwheat plant was simulated by days after sowing (DAS) and leaf area index (LAI), the average values for four growth stages were 0.58, 0.59, 1.10, and 0.74; and soil evaporation coefficient (the ratio of soil evaporation to reference evapotranspiration) was modeled by soil water content at 5-cm depth by dividing the LAI into two stages. The relationship between the ratio of soil evaporation to actual evapotranspiration (E g/ET c) and LAI was decided. It was found that E g/ET c decreased from 1 to 0.3 with the increase in LAI.

Deposition Evaluation of Aerial Electrostatic Spraying System Assembled in Fixed-Wing

<abstract> <bold><sc>Abstract. </sc></bold>There are many difficulties involved with controlling pests and diseases on corn, not least of which include efficiencies relating to process, spraying chemicals, and labor. This study proposes an aerial electrostatic spraying method for the disease and pest control of corn, which is more efficient and economic than previous methods. An aerial electrostatic nozzle embedded with a conical tubular electrode was specifically designed to attach to the fixed-wing aircraft Y5B. Laboratory studies have been conducted to examine the distribution of droplet deposition on the modeled crop targets. Meanwhile, field experiments have also been conducted on the three spray treatments using the aircraft Y5B: electrostatic, non-electrostatic, and rotary sprays. The results showed that compared with non-electrostatic and rotary sprays, the size of the electrostatic spray droplet reduced and the uniformity increased. Also, the coverage of the droplet on the canopy of simulated lab targets increased by 20 and 42 drops·cm^-2. Likewise, the coverage increased 3.71 and 4.33 times on the field targets, when compared to the non-electrostatic and rotary sprays. In particular, there was a significant increase in the number of deposits in the back of the targets. The distribution of the droplet deposition on the vertical canopy showed that the droplet more successfully penetrated the field canopy compared to the same in the lab; and the droplet deposition rate on the middle and bottom of the targets increased significantly. The volume deposition on the middle was highest when using the electrostatic spray application, up to 0.046 μg.cm^-2. The mean deposition calculated was 5.64, 4.26, 3.81 L·ha^-1 for electrostatic, non-electrostatic, and rotary sprays, respectively. The pest control test demonstrated that the cumulative mortality of armyworms was as high as 95.4% under the electrostatic spray treatment, which had better control effects and was more economic than the other two treatments. This study will significantly improve the understanding of the Y5B aircraft aerial electrostatic spraying technique and contribute to the prevention of crop disease and damage.

Assessment of crop foliar nitrogen using a novel dual-wavelength laser system and implications for conducting laser-based plant physiology

Advanced technologies for improved nitrogen (N) fertilizer management are paramount for sustainably meeting future food demands. Green laser systems that measure pulse return intensity can provide more reliable information about foliar N than can traditional passive remote sensing devices during the critical early crop growth stages (e.g., before canopy closure when vegetation and soil signals are spectrally mixed) when further decisions regarding N management can be made. However, current green laser systems are not designed for agricultural applications and only employ a single green laser wavelength, which may limit applications because many factors that require normalization techniques can affect pulse return intensity. Here, we describe the design of a tractor-mountable, green (532nm)- and red (658nm) dual wavelength laser system and evaluate the potential of an additional red reference wavelength to improve laser based estimates of foliar N by calculating laser spectral indices based on ratio combinations of green laser return intensity (GLRI) and red laser return intensity (RLRI). We hypothesized that such laser spectral indices aid in accounting for factors that confound laser based foliar N estimates including variations in leaf angle, measurement distance, soil returns, and mixed edge returns. Leaf level measurements in winter wheat (Triticum aestivum) revealed that the two laser spectral indices improved the relationship with foliar N (r2>0.71, RMSE<0.28%) compared to the sole use of GLRI (r2=0.47, RMSE=0.38%). Laboratory measurements also showed that laser spectral indices reduced the effect of measurement distance on laser readings and allowed leaf returns to be better separated from edge returns and soil returns. However, laboratory measurements showed that laser spectral indices did not account for variations in leaf angle, possibly explaining the weak relationships (r2<0.36, RMSE=0.49%) between foliar N and laser spectral indices observed when employing the laser system under field conditions. In fact, the strongest relationship at the field canopy level was shown for GLRI (r2=0.65, RMSE=0.37%) alone. Laboratory measurements suggest that the better performance of GLRI compared to ratio-based laser spectral indices may result from pronounced differences in the leaf-level bidirectional reflectance distribution factor (BRDFleaf) between the green and red laser wavelengths, thus confounding leaf angle effects so that they are not cancelled when calculating laser spectral indices. This finding suggests that the small spot size of the laser pulses (⩽5mm diameter) interacts with BRDFleaf at very fine scales, therefore causing differential, wavelength-specific scattering effects. Additional study of BRDFleaf at the mm scale is therefore warranted, and should be carefully considered in future development and use of multi-wavelength laser systems for remotely sensing foliar biochemistry.