Performance of variable-orifice nozzles for liquid fertilizer applications

Citation: Sharda, A., Fulton, J. P., & Taylor, R. K. (2016). Performance of variable-orifice nozzles for liquid fertilizer applications. Applied Engineering in Agriculture, 32(3), 347-352. doi:10.13031/aea.32.11428Variable-rate application continues to gain interest among precision agriculture practitioners including the use of crop sensor technology for application of nitrogen in grain crops. For liquid fertilizers, variable-orifice nozzles are being implemented since they provide a much larger nozzle flow range compared to traditional fixed orifice nozzles. However, understanding the performance of variable-orifice nozzles under different field operating conditions has been limited. Therefore, the objective of this study was to evaluate the performance of variable orifice nozzles in support of variable-rate application. Two common variable-orifice nozzles offered by different companies were selected for this study. They were tested over three flow ranges (0.76 to 1.89 L/min) with all tests replicated three times. A commercially available 18.6-m, wet boom sprayer equipped with 37 nozzle bodies was used. Nozzles were numbered but then randomly assigned a position along the boom. To evaluate the performance of an individual nozzle, three random nozzle locations along the spray boom were established for both sets of nozzles. Therefore, 18 tests per replication were required to include the 3 flow rates, 3 different locations, and 2 nozzle types. Once the desired flow rate test was established, tip flow was measured using SpotOn Sprayer Calibrator technology. Tip flows were recorded and statistical analyses performed to evaluate flow uniformity (CV) across the boom but also detect off-rate errors by individual nozzles and locations across the boom. With the exception of a few nozzles, the uniformity across the spray boom, as defined by the CV, was acceptable for both nozzle types over approximately a 2:1 flow range. Both nozzle types were less uniform at the low flow rate. There were three nozzles of each type that resulted in unacceptable flow errors in multiple tests. © 2016 American Society of Agricultural and Biological Engineers

Dynamic Label Assignment for Object Detection by Combining Predicted IoUs and Anchor IoUs

Label assignment plays a significant role in modern object detection models. Detection models may yield totally different performances with different label assignment strategies. For anchor-based detection models, the IoU (Intersection over Union) threshold between the anchors and their corresponding ground truth bounding boxes is the key element since the positive samples and negative samples are divided by the IoU threshold. Early object detectors simply utilize the fixed threshold for all training samples, while recent detection algorithms focus on adaptive thresholds based on the distribution of the IoUs to the ground truth boxes. In this paper, we introduce a simple while effective approach to perform label assignment dynamically based on the training status with predictions. By introducing the predictions in label assignment, more high-quality samples with higher IoUs to the ground truth objects are selected as the positive samples, which could reduce the discrepancy between the classification scores and the IoU scores, and generate more high-quality boundary boxes. Our approach shows improvements in the performance of the detection models with the adaptive label assignment algorithm and lower bounding box losses for those positive samples, indicating more samples with higher-quality predicted boxes are selected as positives

RES-Q: Robust Outlier Detection Algorithm for Fundamental Matrix Estimation

Detection of outliers present in noisy images for an accurate fundamental matrix estimation is an important research topic in the field of 3-D computer vision. Although a lot of research is conducted in this domain, not much study has been done in utilizing the robust statistics for successful outlier detection algorithms. This paper proposes to utilize a reprojection residual error-based technique for outlier detection. Given a noisy stereo image pair obtained from a pair of stereo cameras and a set of initial point correspondences between them, reprojection residual error and 3-sigma principle together with robust statistic-based Qn estimator (RES-Q) is proposed to efficiently detect the outliers and estimate the fundamental matrix with superior accuracy. The proposed RES-Q algorithm demonstrates greater precision and lower reprojection residual error than the state-of-the-art techniques. Moreover, in contrast to the assumption of Gaussian noise or symmetric noise model adopted by most previous approaches, the RES-Q is found to be robust for both symmetric and asymmetric random noise assumptions. The proposed algorithm is experimentally tested on both synthetic and real image data sets, and the experiments show that RES-Q is more effective and efficient than the classical outlier detection algorithms

Development and evaluation of an automated spray patternator using digital liquid level sensors

Citation: Luck, J. D., Schaardt, W. A., Forney, S. H., & Sharda, A. (2016). Development and evaluation of an automated spray patternator using digital liquid level sensors. Applied Engineering in Agriculture, 32(1), 47-52. doi:10.13031/aea.32.11381The purpose of this study was to develop and evaluate an automated spray pattern measurement system which utilized digital liquid level sensors to quantify the coefficient of variation (CV) for different nozzle configurations. The overall system was designed to measure nozzle effluent in 25 mm divisions from 38.1 to 76.2 cm in width for multiple nozzle configurations with a total patternator surface width of 3.05 m. The patternator surface and data collection system were designed and developed to achieve three primary goals: patternator surface division accuracy, data collection system accuracy, and data collection system repeatability. Patternator surface measurements indicated an average standard deviation of approximately 0.1 mm (0.4%) which would not contribute significantly to spray pattern CV estimates. To quantify the measurement accuracy, the automated system was compared to manual data collection using weights collected from graduated cylinders. Statistical analysis revealed no difference (p > 0.05) between CV estimates from the manual and automated data collection methods. The average difference in CV between the two methods was 0.15% which considered 12 tests per method. Repeatability was also a primary concern, the standard deviation among CV values for tests conducted with the automated system was only 0.35%. The evaluation of the system provided confidence that suitable results would be acquired for different nozzle configurations consisting of acceptable or relatively poor spray patterns. © 2016 American Society of Agricultural and Biological Engineers

Generating ‘As-Applied’ Pesticide Distribution Maps from a Self-Propelled Agricultural Sprayer Based on Nozzle Pressure Data

The application of pre-emergence, post-emergence, and burn-down herbicides (i.e., glyphosate) continues to increase as producers attempt to reduce both negative environmental impacts from tillage and input costs from labor, machinery and materials. The use of precision agriculture technologies such as automatic boom section control allows producers to reduce off-target application when applying herbicides. While automatic boom section control provides benefits, pressure differences across the spray boom resulting from boom section actuation can lead to off-rate application errors. Off-rate errors may also result from spray rate controller compensation for ground speed changes and velocity variation across the spray boom during turning movements. This project focuses on quantifying accumulated pesticide application for three fields located in Central Kentucky. GPS coordinates were collected along with nozzle pressure data (at 13 nozzle locations) at one second intervals as the sprayer traversed the study fields. The method previously developed by Luck et al. (2009) was used to calculate coverage areas for the control sections along the spray boom in MS Excel. Nozzle discharge flow rates were estimated from the nozzle pressure data (based on manufacturer calibration information) which was then incorporated into MS Excel to determine the rate of pesticide applied to the fields. Results indicate the majority of each field received application rates at or below the target rate. Only 34.2%, 33.9%, and 22.9% of Fields 1, 2, and 4, respectively, received application rates at the target rate +/- 10% during these postemergence treatments. The goal of this project was develop distribution maps to better understand the effects of boom section control and turning movements on herbicide accumulation

Generating ‘As-Applied’ Pesticide Distribution Maps from a Self-Propelled Agricultural Sprayer Based on Nozzle Pressure Data

The application of pre-emergence, post-emergence, and burn-down herbicides (i.e., glyphosate) continues to increase as producers attempt to reduce both negative environmental impacts from tillage and input costs from labor, machinery and materials. The use of precision agriculture technologies such as automatic boom section control allows producers to reduce offtarget application when applying herbicides. While automatic boom section control provides benefits, pressure differences across the spray boom resulting from boom section actuation can lead to offrate application errors. Off-rate errors may also result from spray rate controller compensation for ground speed changes and velocity variation across the spray boom during turning movements. This project focuses on quantifying accumulated pesticide application for three fields located in Central Kentucky. GPS coordinates were collected along with nozzle pressure data (at 13 nozzle locations) at one second intervals as the sprayer traversed the study fields. The method previously developed by Luck et al. (2009) was used to calculate coverage areas for the control sections along the spray boom in MS Excel. Nozzle discharge flow rates were estimated from the nozzle pressure data (based on manufacturer calibration information) which was then incorporated into MS Excel to determine the rate of pesticide applied to the fields. Results indicate the majority of each field received application rates at or below the target rate. Only 34.2%, 33.9%, and 22.9% of Fields 1, 2, and 4, respectively, received application rates at the target rate +/- 10% during these postemergence treatments. The goal of this project was develop distribution maps to better understand the effects of boom section control and turning movements on herbicide accumulation

Real-Time Pressure and Flow Dynamics Due to Boom Section and Individual Nozzle Control on Agricultural Sprayers

Most modern spray controllers when coupled with a differential global positioning system (DGPS) receiver can provide automatic section or swath (boom section or nozzle) control capabilities that minimize overlap and application into undesirable areas. This technology can improve application accuracy of pesticides and fertilizers, thereby reducing the number of inputs while promoting environmental stewardship. However, dynamic system response for sprayer boom operation, which includes cycling or using auto-swath technology, has not been investigated. Therefore, a study was conducted to develop a methodology and subsequently perform experiments to evaluate tip pressure and system flow variations on a typical agricultural sprayer equipped with a controller that provided both boom section and nozzle control. To quantify flow dynamics during boom section or nozzle control, a testing protocol was established that included three simulation patterns under both flow compensation and no-compensation modes achieved via the spray controller. Overall system flow rate and nozzle tip pressure at ten boom locations were recorded and analyzed to quantify pressure and flow variations. Results indicated that the test methodology generated sufficient data to analyze nozzle tip pressure and system flow rate changes. The tip pressure for the compensated section control tests varied between 6.7% and 20.0%, which equated to an increase of 3.7% to 10.6% in tip flow rate. The pressure stabilization time when turning boom sections and nozzles off approached 25.2 s but only approached 15.6 s when turning them back on for the flow compensation tests. Although extended periods were required for the tip pressure to stabilize, the system flow rate typically stabilized in less than 7 s. The tip flow rate was consistently higher (up to 10.6%) than the target flow rate, indicating that system flow did not truly represent tip flow during section control. The no-compensation tests exhibited tip pressure increases up to 35.7% during boom and nozzle control, which equated to an 18.2% increase in tip flow. Therefore, flow compensation over no-compensation had better control of tip flow rate. A consistent difference existed in dynamic pressure response between boom section and nozzle control. Increased tip pressure and delayed pressure stabilization times indicated that application variability can occur when manually turning sections on and off or implementing auto-swath technology, but further testing is needed to better understand the effect on application accuracy of agricultural sprayers

On the Real-Time Semantic Segmentation of Aphid Clusters in the Wild

Aphid infestations can cause extensive damage to wheat and sorghum fields and spread plant viruses, resulting in significant yield losses in agriculture. To address this issue, farmers often rely on chemical pesticides, which are inefficiently applied over large areas of fields. As a result, a considerable amount of pesticide is wasted on areas without pests, while inadequate amounts are applied to areas with severe infestations. The paper focuses on the urgent need for an intelligent autonomous system that can locate and spray infestations within complex crop canopies, reducing pesticide use and environmental impact. We have collected and labeled a large aphid image dataset in the field, and propose the use of real-time semantic segmentation models to segment clusters of aphids. A multiscale dataset is generated to allow for learning the clusters at different scales. We compare the segmentation speeds and accuracy of four state-of-the-art real-time semantic segmentation models on the aphid cluster dataset, benchmarking them against nonreal-time models. The study results show the effectiveness of a real-time solution, which can reduce inefficient pesticide use and increase crop yields, paving the way towards an autonomous pest detection system

Comparison of 2-way versus metered 3-way boom shut-off valves for automatic section control on agricultural sprayers

Modern spray rate controllers along with technologies such as automatic section control (ASC) provide benefits such as overlap reduction on agricultural sprayers. However, product (liquid) dynamics within the boom plumbing affect off-rate errors and application uniformity during rate changes and ASC actuation. Therefore, this study was conducted to compare nozzle flow stability and uniformity across the boom when using two different boom shut-off valves (2-way and metered 3-way) on an 18.3-m sprayer boom. Pressure transducers were mounted at 1) the boom manifold, 2) randomly at 12 nozzle bodies across the spray boom, and 3) upstream and downstream of the flow regulating valve. Effective system flow rate was measured using two flow meter(s), one located upstream of the boom control valves (2-way or metered 3-way) and another mounted to measure the tank return flow for the metered 3-way boom valve. Measured nozzle pressure was converted to nozzle flow using the manufacturer’s pressure-flow data. Results indicated that the 2-way boom versus metered 3-way valve response was significantly different. Significant differences in damping ratios were found when exiting (under-damped) and reentering (over-damped) of spray zones. For the metered 3-way boom valve configuration, nozzle flow settled faster (0.1 to 4.2 s) virtually eliminating off-rate errors whereas the 2-way boom valve configuration took up to 34.3 s to settle with off-rate errors ranging from 3.3% to 11.5%. The delayed nozzle flow settling times were associated with pressure settling (0.7 to 31.4 s) downstream of the regulating valve for the 2-way configuration. Ground speed and point row angle impacted nozzle flow settling times and off-rate errors. The increase in ground speed and point row angle increased nozzle flow settling time for the 2-way valve setup, except that acceleration decreased settling times when exiting spray zones. The delayed response contributed to off-rate time which decreased as the sprayer accelerated and point row angle decreased for both the 2-way (1.7 to 19.3 s) and metered 3-way (2.1 to 4.4 s) boom shut-off valve setups

Spatio-temporal evaluation of plant height in corn via unmanned aerial systems

Detailed spatial and temporal data on plant growth are critical to guide crop management. Conventional methods to determine field plant traits are intensive, time-consuming, expensive, and limited to small areas. The objective of this study was to examine the integration of data collected via unmanned aerial systems (UAS) at critical corn (Zea mays L.) developmental stages for plant height and its relation to plant biomass. The main steps followed in this research were (1) workflow development for an ultrahigh resolution crop surface model (CSM) with the goal of determining plant height (CSM-estimated plant height) using data gathered from the UAS missions; (2) validation of CSM-estimated plant height with ground-truthing plant height (measured plant height); and (3) final estimation of plant biomass via integration of CSM-estimated plant height with ground-truthing stem diameter data. Results indicated a correlation between CSM-estimated plant height and ground-truthing plant height data at two weeks prior to flowering and at flowering stage, but high predictability at the later growth stage. Log–log analysis on the temporal data confirmed that these relationships are stable, presenting equal slopes for both crop stages evaluated. Concluding, data collected from low-altitude and with a low-cost sensor could be useful in estimating plant height.Sociedad Argentina de Informática e Investigación Operativ