Site-specific Herbicide Applications Research Articles

Teilflächenspezifische Ausbringung von Fungiziden und Herbiziden

It is evident through many practical tests in past years that site-specific application of herbicides and fungicides can have ecological and economical advantages. The prerequisites for economical success are that the necessary sensors and application tech

Site-Specific Weed Management in Corn (Zea mays)1

Site-specific weed management can increase crop production efficiency by minimizing herbicide input costs without compromising crop yields. A reduction in herbicide inputs resulting from site-specific weed management may also decrease the probability level of nonpoint pollution compared with conventional herbicide applications. A 4.5-ha field was selected to compare site-specific and conventional weed management techniques in 1997 and 1998 at Knoxville, TN. Variable rate applications (VRAs) of atrazine preemergence (PRE) followed by dicamba postemergence (POST) were investigated for the reduction of herbicide inputs and their resulting impact on weed control and corn yield. VRAs of atrazine were on the basis of weed density data collected in 1996. VRAs of dicamba were according to common cocklebur density evaluations within the field. Compared with conventional applications, atrazine usage was decreased by 43 and 32% in the site-specific application treatments in 1997 and 1998, respectively. VRAs of dicamba reduced herbicide inputs by greater than 45% for 1997 and 1998. Corn yields were similar for the conventional and site-specific treatments in both years. On the basis of these data, site-specific herbicide applications have the greatest potential and least risk for managing weeds when POST or PRE POST variable rate herbicide applications are used.Nomenclature: Atrazine; dicamba; common cocklebur, Xanthium strumarium L. #3 XANST; corn, Zea mays L. ‘Dekalb 689’.Additional index words: Brachiaria platyphylla (Griseb.) Nash, broadleaf signalgrass, geographical information systems, global positioning systems, variable rate application.Abbreviations: DGPS, differential global positioning system; GIS, geographic information system; OM, organic matter; POST, postemergence; PRE, preemergence; VRA, variable rate application.

Weed–Crop Discrimination Using Remote Sensing: A Detached Leaf Experiment1

Mapping weed infestations in an annual crop has implications not only for site-specific herbicide applications but also for planning future management strategies and understanding weed ecology. A controlled laboratory experiment, involving detached leaves, was conducted to investigate the potential to discriminate two crop and five weed species using hyperspectral and multispectral remote sensing. Stepwise discriminant function analyses showed that reflectance in the visible and “red-edge” regions of the spectrum were consistently required for species discrimination. The seven species were correctly identified 90 and 89% of the time using the hyperspectral and multispectral data, respectively, and the classification rules derived from discriminant function analyses. Errant species prediction with the hyperspectral data resulted in a grass being predicted as a grass and a broadleaf as a broadleaf. However, for multispectral data, incorrect classifications were more serious because errant predictions someti...

Development of an image processing system and a fuzzy algorithm for site-specific herbicide applications

In precision farming, image analysis techniques can aid farmers in the site-specific application of herbicides, and thus lower the risk of soil and water pollution by reducing the amount of chemicals applied. Using weed maps built with image analysis techniques, farmers can learn about the weed distribution within the crop. In this study, a digital camera was used to take a series of grid-based images covering the soil between rows of corn in a field in southwestern Quebec in May of 1999. Weed coverage was determined from each image using a “greenness method” in which the red, green, and blue intensities of each pixel were compared. Weed coverage and weed patchiness were estimated based on the percent of greenness area in the images. This information was used to create a weed map. Using weed coverage and weed patchiness as inputs, a fuzzy logic model was developed for use in determining site-specific herbicide application rates. A herbicide application map was then created for further evaluation of herbicide application strategy. Simulations indicated that significant amounts of herbicide could be saved using this approach.

Site-Specific Herbicide Decision Model to Maximize Profit in Winter Wheat

A user-friendly computerized agricultural herbicide decision model has been developed for selecting profitable site-specific herbicide applications in winter wheat. The model is based on 6 years of field research in southeastern Washington State, USA. The model calibrates herbicide applications to management unit weed densities, soil organic matter, soil moisture, and preceding management, as well as to expected input and output prices. The model increased broadleaf herbicide rates by an average 0.65 of label rates compared to the recommendations by farmers and weed science professionals, but cut the more expensive grass herbicides by an average 0.56 of label rates. The model increased average projected profitability, excluding model application costs, by 65% compared to four other criteria for determining application rates. The profitability increase relative to local farmers was 19%. Both the model and the cooperating farmers properly chose to use no grass herbicides on the study sites, but the weed science experts chose to use up to 1.0 of label rates. The estimated payoff from using the model substantially exceeded the cost of weed scouting and other information collection. Determining economically optimal sampling and management units is an important challenge for the adoption of precision agriculture models like the one developed in this study.

AE—Automation and Emerging Technologies: A Vegetation Localization Algorithm for Precision Farming

The primary goal of this study was to develop the image processing component of a weed detection and mapping system that can be applied to precision farming. The image processing algorithm first located the green objects in the digital image, then calculated weed density based on the greenness ratio. The greenness ratio was the portion of an image in which the green intensity was larger than the red and blue intensities. Some smoothing filters were also investigated to remove noise from the image. Three approaches to determine the greenness ratio were evaluated and compared to the manual survey using a planimeter. With the similar greenness ratios obtained from these approaches, the approach using MATLAB built-in function ‘vectorization of loops’ gave comparable results to those using a planimeter in the shortest amount of time, 0·8s per image, compared to 83–88s per image by the other two approaches applying the greenness method to different image formats without the vectorization function. Using digital images of a maize field taken in 1999, the weed distribution on a portion of the field was mapped. The results showed that only 59% of the maize field required full herbicide application based on having a weed density of 5% or more. The proposed image processing method is a simple and fast way to detect weeds with a commercial digital camera. It can become an important component of a weed detection and mapping system by assisting in site-specific application of herbicides in order to reduce herbicide costs and environmental pollution.

Site-Specific Weed Control in Maize, Sugar Beet, Winter Wheat, and Winter Barley

A four-year study of site-specific weed control is presented in this paper. Weed seedling distribution was sampled and mapped prior to and after post-emergence herbicide application in four fields planted with maize, sugar beets, winter wheat and winter barley, rotating on one site. Herbicides and other weed control strategies were applied site-specifically according to the spatial variation of weed populations. Different decision algorithms were used for chemical weed control methods in each crop. A weed treatment map was created to direct location and dosage of herbicide application. The sprayer was coupled with a differential Global Positioning System (DGPS). The solenoid valves of the sprayer were opened automatically when the tractor entered a weed patch characterized in the weed treatment map. For site specific herbicide application, a patch sprayer was developed that allowed variable rate application and the selective control of each section of the spray boom.

Weed Detection Using Canopy Reflection

For site-specific application of herbicides, automatic detection and evaluation of weeds is desirable. Since reflectance of crop, weeds and soil differs in the visual and near infrared wavelengths, there is potential for using reflection measurements at different wavelengths to distinguish between them. Reflectance spectra of crop and weed canopies were used to evaluate the possibilities of weed detection with reflection measurements in laboratory circumstances. Sugarbeet and maize and 7 weed species were included in the measurements. Classification into crop and weeds was possible in laboratory tests, using a limited number of wavelength band ratios. Crop and weed spectra could be separated with more than 97% correct classification. Field measurements of crop and weed reflection were conducted for testing spectral weed detection. Canopy reflection was measured with a line spectrograph in the wavelength range from 480 to 820 nm (visual to near infrared) with ambient light. The discriminant model uses a limited number of narrow wavelength bands. Over 90% of crop and weed spectra can be identified correctly, when the discriminant model is specific to the prevailing light conditions.

DEVELOPMENT OF NEURAL NETWORKS FOR WEED RECOGNITION IN CORN FIELDS

The main objective of this project was to develop a weed recognition system based on artificial neural networksto assist in the precision application of herbicides in corn fields. Digital images were collected in May 1998 using acommercially available digital camera. The intensities of the three primary colors (red, green, and blue) were compared foreach pixel of the images. The three intensities of a pixel remained unchanged when, in the pixel, the green intensity was greaterthan each of the other two; otherwise, the three intensities of the pixel were set to zero. Background objects, except plants,were thus removed from the images. The resulting pixel intensities of the modified images were used as the inputs for LearningVector Quantization (LVQ) artificial neural networks (ANNs). ANNs were trained to distinguish corn from weeds, as well asto differentiate between weed species. The success rate for a single ANN in distinguishing a given weed species from cornwas as high as 90%, and as high as 80% in distinguishing any of four weed species from corn. Better success rates might beobtainable with more elaborate schemes for data input and/or structural improvements such as cascading. Theimageprocessing time for the ANNs was as short as 0.48 s per image, thus making it useful for realtime data processingand application of herbicides. The development of such ANNs for weed recognition could be useful in precision farming toguide sitespecific herbicide application and ultimately reduce the total amount of herbicide applied as well as lowering therisk of pollution.

Evaluation of site-specific weed management using a direct-injection sprayer

Abstract Targeting weed patches for site-specific herbicide applications potentially represents cost savings for operators, reduction in environmental herbicide effects, and increased efficiency of weed control. An experiment was initiated in a no-till corn field in Ontario, Canada, in 1998 and was continued in rotation with no-till soybeans in 1999. Weeds were intensively scouted, and distribution maps of the most common weeds (field horsetail, spiny sowthistle, dandelion, and common lambsquarters) were generated for both years. A prescription map for each plot was made using the weed density maps. Treatment decisions were based on a weed threshold value of 1 shoot m−2. Four herbicide treatments were compared: a conventional broadcast, a site-specific application targeting weed patches only, and two combinations of broadcast and site-specific applications. Treatments were applied using a direct-injection sprayer. Efficacy of weed control and yield were compared among treatments. In 1998 and 1999 there we...

AERIAL CIR REMOTE SENSING FOR WEED DENSITY MAPPING IN A SOYBEAN FIELD

Accurate weed maps are essential for the success of sitespecific herbicide application using mapbasedvariablerate sprayers. In this study, remotely sensed images acquired using an airborne digital color infrared (CIR) sensorwere used for mapping and modeling the spatial distribution of weed infestation density within a soybean field. The effectof spatial positioning error associated with data on resolution requirements and mapping accuracy was also studied.Vegetative indices developed from the threeband CIR image showed strong correlation with spatial weed density. The bestcorrelation was observed at the spatial resolutions of 4.5 m/pixel to 5.3 m/pixel, which was lower than the actual dataresolutions. Higher modeling accuracies observed at lower resolutions were caused by the positioning error associated withboth aerial imaging data and groundtruth data. At this resolution, the weed density models developed using an artificialneural network resulted in R 2 values of 0.87 and 0.83. This model mapped the spatial distribution of weed density with anR 2 value of 0.58 for a field not used in modeling.

Economic comparison of broadcast and site-specific herbicide applications in nontransgenic and glyphosate-tolerantGlycine max

Abstract Weed population estimates were collected from four Glycine max fields during the summers of 1997 and 1998. Seedling weed populations were sampled using a regular coordinate system on a grid either 50 by 50, 30 by 30, or 10 by 10 m. MSU-HERB and Mississippi Herbicide Application Decision Support System (HADSS) (yield loss prediction and herbicide recommendation models for G. max) were used to determine the estimated net gain resulting from simulated herbicide applications at each sample location in each field. When necessary, the appropriate data points from the 10- by 10-m grid were removed to form population data sets on grids 20 by 20, 40 by 40, and 80 by 80 m. The objectives of this research were to compare estimated economic returns of site-specific herbicide management and broadcast herbicide management in nontransgenic and glyphosate-tolerant G. max and to evaluate the effects of various weed sampling intensities on estimated economic returns from site-specific herbicide applications. Site-...

Crop/Weed Outcomes from Site-Specific and Uniform Soil-Applied Herbicide Applications

While uniform broadcast application (BC) of soil-applied herbicides is the norm, advances in geospatial technologies have enabled the deployment of site-specific herbicide application (SS). Since there are several, largely-untested decision rules for SS herbicide use, the objective of this work was to evaluate crop/weed outcomes and isoxaflutole use for a number of BC and SS strategies. Field experiments were established where isoxaflutole dose response functions were quantified from early-season Zea mays (L.), Sorghum bicolor (L.) Moench., and Abutilon theophrasti Medic. response data at multiple plots (64 in 1999; 62 in 2000) throughout a variable field. These data were then used to infer crop and weed outcomes from simulated application strategies. While BC and SS strategies that relied on the product label were similar in terms of total herbicide use, extent of crop tolerance, and A. theophrasti efficacy, the SS strategy resulted in a significant redistribution of herbicide. Using biologically effective doses (ED) resulted in the highest efficacy and herbicide use was highly species-dependent. By using a historical weed map of the field to guide herbicide application, herbicide use could be reduced some 20–48% when following the product label where seedlings were present, or >90% when using the ED for A. theophrasti. In order to maximize the potential agronomic benefits of SS, biological and spatial information of both the weed and soil should be taken into account.

Two-year weed seedling population responses to a post-emergent method of site-specific weed management.

Field experiments were conducted to determine how a site-specific weed management practice in Zea mays L. influenced the numerical and spatial distribution of a naturally occurring weed infestation in Z. mays and the succeeding Beta vulgaris L. crop. Compared to conventional broadcast herbicide applications, site-specific herbicide applications reduced herbicide load by 11.5 and 98.0% in two separate Z. mays fields. The broad range in outcomes was attributed to the spatial aggregation and density of target weed populations. While herbicide use was successfully reduced at field locations with low weed density, most survivors of multiple control tactics were in locations with the highest initial density. A greater understanding of interactions between weed management and weed density would increase the likelihood that site-specific weed management offers long-term improvements over conventional approaches.

EVALUATION OF A FLOW CONTROL SYSTEM FOR SITE-SPECIFIC HERBICIDE APPLICATIONS

An electronic flow control system for site-specific herbicide applications was tested for steady stateperformance. The control system used spray nozzles coupled with solenoid valves, regulated using pulse-widthmodulation at 10 Hz and duty cycles of 10 to 100% to control the flow rate. The controller could vary the nozzle flow ratein the ratio of up to 9.5 to 1 without a significant change in the spray pattern. Droplet size distribution of the variable ratesystem was fairly constant at duty cycles of 25 to 100%. The Volume Median Diameter (VMD) at a duty cycle of 10% wassignificantly different from the rest. Response delay was small and suitable for high-speed herbicide applications. Theuniformity of spray deposition along the orthogonal direction (along travel direction) decreased dramatically as the dutycycle decreased and travel speed increased. The variable flow nozzle could be used on existing sprayers for maintainingthe application rate as the speed changes by controlling the flow rate. For local sensor based site-specific herbicideapplication, the controller has to be modified to overcome banded spray deposition at high travel speed and low dutycycle combinations.

A FEASIBILITY STUDY OF DIRECT INJECTION FOR VARIABLE-RATE HERBICIDE APPLICATION

Variable-rate application of herbicides based on soil properties and crop yield potential may be a viableapproach to reducing the quantities of herbicides used in crop production. Application accuracy of direct injection equipment is an important issue for variable-rate application. A simulation model was developed using SLAM II to assess the performance of a direct injection sprayer used for site-specific application of preemergence herbicides in corn. Field data from a university research farm were used as input to the model (i.e., soil texture, organic matter content, and yield potential). Several factors such as in-line mixing location, hose diameter, nozzle spacing and size, and ground speed were investigated for their effects on system performance. A complement of system parameters was identified to reduce application errors. Multiple system errors were combined using the mean square error approach. Results of the simulation were input to a GIS software to generate herbicide application rate maps and the corresponding error rate maps. Application errors for direct injection systems were as high as 40% for mistreated areas of the field, with changes in chemical concentration at the remote nozzles occurring after as much as 80 m of travel past the point of a step change of the input command to the controller. Recommendations for reducing delay times at the nozzle include moving the in-line mixing location close to the boom and using smaller line sizes to reduce line volume, without appreciably increasing pressure drop.