scholarly journals Weed Mapping in Vineyards Using RGB-D Perception

2021 ◽  
Vol 9 (1) ◽  
pp. 30
Author(s):  
Dimitrios Kateris ◽  
Damianos Kalaitzidis ◽  
Vasileios Moysiadis ◽  
Aristotelis C. Tagarakis ◽  
Dionysis Bochtis
Keyword(s):  
Weed Management ◽  
Management Practices ◽  
Field Conditions ◽  
Yield Losses ◽  
Weed Mapping ◽  
Significant Yield ◽  
Different Levels

Weed management is one of the major challenges in viticulture, as long as weeds can cause significant yield losses and severe competition to the cultivations. In this direction, the development of an automated procedure for weed monitoring will provide useful data for understanding their management practices. In this work, a new image-based technique was developed in order to provide maps based on weeds’ height at the inter-row path of the vineyards. The developed algorithms were tested in many datasets from vineyards with different levels of weed development. The results show that the proposed technique gives promising results in various field conditions.

scholarly journals UAV-Assisted Thermal Infrared and Multispectral Imaging of Weed Canopies for Glyphosate Resistance Detection

2021 ◽  
Vol 13 (22) ◽  
pp. 4606
Author(s):  
Austin Eide ◽  
Cengiz Koparan ◽  
Yu Zhang ◽  
Michael Ostlie ◽  
Kirk Howatt ◽  
...  
Keyword(s):  
Maximum Likelihood ◽  
Weed Management ◽  
Management Practices ◽  
Multispectral Imaging ◽  
Glyphosate Resistance ◽  
Random Trees ◽  
Field Conditions ◽  
Support Vector ◽  
Classification Methods ◽  
Continuous Growth

The foundation of contemporary weed management practices in many parts of the world is glyphosate. However, dependency on the effectiveness of herbicide practices has led to overuse through continuous growth of crops resistant to a single mode of action. In order to provide a cost-effective weed management strategy that does not promote glyphosate-resistant weed biotypes, differences between resistant and susceptible biotypes have to be identified accurately in the field conditions. Unmanned Aerial Vehicle (UAV)-assisted thermal and multispectral remote sensing has potential for detecting biophysical characteristics of weed biotypes during the growing season, which includes distinguishing glyphosate-susceptible and glyphosate-resistant weed populations based on canopy temperature and deep learning driven weed identification algorithms. The objective of this study was to identify herbicide resistance after glyphosate application in true field conditions by analyzing the UAV-acquired thermal and multispectral response of kochia, waterhemp, redroot pigweed, and common ragweed. The data were processed in ArcGIS for raster classification as well as spectral comparison of glyphosate-resistant and glyphosate-susceptible weeds. The classification accuracy between the sensors and classification methods of maximum likelihood, random trees, and Support Vector Machine (SVM) were compared. The random trees classifier performed the best at 4 days after application (DAA) for kochia with 62.9% accuracy. The maximum likelihood classifier provided the highest performing result out of all classification methods with an accuracy of 75.2%. A commendable classification was made at 8 DAA where the random trees classifier attained an accuracy of 87.2%. However, thermal reflectance measurements as a predictor for glyphosate resistance within weed populations in field condition was unreliable due to its susceptibility to environmental conditions. Normalized Difference Vegetation Index (NDVI) and a composite reflectance of 842 nm, 705 nm, and 740 nm wavelength managed to provide better classification results than thermal in most cases.

scholarly journals Weed Interference and Control in Cowpea Production: A Review

2017 ◽  
Vol 9 (12) ◽  
pp. 11 ◽  
Author(s):  
O. Adewale Osipitan
Keyword(s):  
Weed Control ◽  
Weed Management ◽  
Management Practices ◽  
Control Method ◽  
Insect Pests ◽  
Wide Spectrum ◽  
Growth Stages ◽  
Yield Losses ◽  
Weed Interference ◽  
Weed Removal

In spite of the great economic potential of cowpea as both domestic and commercial crop, a number of constraints, which include insect pests, diseases and weeds, limits its production in West and many parts of Africa. Weeds reduced cowpea yield and value by competing for light, water and nutrients. Cowpea suffers from weeds particularly when the crop is in the early growth stages before ground cover. Yield losses cause by weeds alone in cowpea production can be as high as 76% depending on the cowpea cultivar, environment and weed management practices. A timely weed removal at the critical period, which falls within the first 40 days of cowpea growth, would help to prevent an unacceptable yield. Weed management in cowpea has been with low technology. Hand weeding is the most widely used weed control method in cowpea but they are usually expensive and labour intensive. Cultural practices such as narrow row spacing and planting of early maturing varieties are also used for weed control in cowpea. Herbicides, which are relatively easy to use and less expensive, have not been widely adopted for weed control in cowpea. There are limited number of selective herbicides with wide spectrum for weed control in cowpea. However, an integrated practices that involved pre-emergence weed control using herbicides or physical weeding, and a supplementary weed removal that would ensure weed control up to 40 days after cowpea emergence could substantially prevent yield losses associated with weed interference.

scholarly journals Weed Mapping as a Component of Integrated Pest Management in Cranberry Production

1995 ◽  
Vol 5 (4) ◽  
pp. 302-305 ◽  
Author(s):  
Mary Jane Else ◽  
Hilary A. Sandler ◽  
Scott Schluter
Keyword(s):  
Integrated Pest Management ◽  
Pest Management ◽  
Weed Management ◽  
Management Practices ◽  
Management Strategies ◽  
Control Program ◽  
Vaccinium Macrocarpon ◽  
Weed Mapping ◽  
Mapping System ◽  
Mapping Systems

A system of mapping weed infestations in cranberries (Vaccinium macrocarpon Ait.) was developed that enables growers to incorporate integrated pest management practices into their weed control program. This system provides growers with information on the location of weeds and the area of weed patches, but differs from other weed mapping systems in that information on control priorities is included on the maps. Weed management efforts can then be directed to the most economically damaging weeds first. The mapping system also provides growers with a permanent record that can be used to communicate with staff and to evaluate weed management strategies.

scholarly journals ECOLOGICAL/CULTURAL MEASURES OF WEED MANAGEMENT FOR SUSTAINABLE AGRICULTURE

2021 ◽  
Vol 3 (2) ◽  
pp. 41-43
Author(s):  
Sirpat Badhai ◽  
Aman Kumar Gupta
Keyword(s):  
Weed Management ◽  
Agricultural Production ◽  
Management Practices ◽  
Crop Protection ◽  
Developed Countries ◽  
Yield Losses ◽  
Least Developed Countries ◽  
Potential Yield ◽  
Crop Species ◽  
Direct Seeded

The weed is a plant that grows where it is undesired or in its place. Weeds are unwanted plants that are not known to be economically important. Weeds are plants that are unwanted in a given situation and may be dangerous, harmful or economically detrimental. Weeds have serious problems when it comes to agricultural production. It is estimated that weeds generally cause a 25% loss of agricultural production in the least developed countries, a 10% loss in the least developed countries and a 5% loss in most developed countries. Weeds loses are depend upon location, crop and types of soil. The study found that potential yield losses were significant for soybeans (50-76%) and peanuts (45-71%). Largest variability in potential yield losses were observed among locations in case of direct seeded rice (15-66%) & maize (18-65%). In similar cases weeds are reduced 66% yield of Chilly and the loss of N through weeds is about 150 kg per ha. Weeds losses alone in 10 major crops of India viz transplanted rice (13.8%), wheat (18.6%), direct-seeded rice (21.4%), mustard (21.4%), sesame (23.7%), sorghum (25.1%), maize (25.3%), Pearlmillet (27.6%), Greengram (30.8%), soybean (31.4%) and groundnut (35.8%). Weed control practices are extremely important to Indian agricultural production. Many more tools and practices are adopted for crop protection q like crop species, crop variety/cultivars, sowing of crop (time, rate of sowing, row spacing and method), crop rotation, trap and catch crops, cropping practice, irrigation time & method are suitable practices under cultural/ecological measures of weed management. Cropping practices are also known as environmentally responsible weed management practices. Environmentally sound weed management methods are chemical-free and weed management tools-free.

scholarly journals 627 PB 457 RELAY-INTERPLANTING COVER CROPS IN SWEET CORN

HortScience ◽  
1994 ◽  
Vol 29 (5) ◽  
pp. 522c-522
Author(s):  
Tom TenPas ◽  
John Luna
Keyword(s):  
Zea Mays ◽  
Cover Crops ◽  
Weed Management ◽  
Cover Crop ◽  
Management Practices ◽  
Sweet Corn ◽  
Weed Competition ◽  
Corn Yield ◽  
Significant Yield ◽  
Block Experiment

The effect on corn yield of interplanting two different cover crops, Trifolium repens, and Lolium perens into sweet corn, Zea mays, at 4 different times from corn planting was examined. Sweet corn was planted in 30 inch rows, and the cover crop was planted 0, 7, 14, and 21 days afterwards. The study was designed as a complete randomized block experiment with 4 replications. Weed management practices included pre-emergent herbicides and cultivation only treatments. No significant yield differences in corn yields were detected (alpha=.05). Most of the plots had very little weed competition, including those with no herbicide treatment. Earlier planted cover crops were better established at time of corn harvest. Additional work is needed to examine this practice in conditions of greater weed competion.

Weed Management in Small Grains Harvested for Grain

EDIS ◽  
2020 ◽  
Vol 2020 (3) ◽  
Author(s):  
Jason Ferrell ◽  
Gregory MacDonald ◽  
Pratap Devkota
Keyword(s):  
Weed Control ◽  
Weed Management ◽  
Chemical Control ◽  
Management Practices ◽  
Good Management ◽  
Small Grains ◽  
Crop Competition

Successful weed control in small grains involves using good management practices in all phases of production. In Florida, winter weeds compete with small grains for moisture, nutrients, and light, with the greatest amount of competition occurring during the first six to eight weeks after planting. Weeds also cause harvest problems the following spring when the small grain is mature. This 4-page publication discusses crop competition, knowing your weeds, and chemical control. Written by J. A. Ferrell, G. E. MacDonald, and P. Devkota, and published by the UF/IFAS Agronomy Department, revised May 2020.

Weed Management in Peanuts

EDIS ◽  
2020 ◽  
Vol 2020 (3) ◽  
Author(s):  
Pratap Devkota
Keyword(s):  
Weed Control ◽  
Weed Management ◽  
Management Practices ◽  
Application Rate ◽  
Good Management ◽  
Peanut Production

Successful weed control in peanuts involves use of good management practices in all phases of peanut production. This 11-page document lists herbicide products registered for use in Florida peanut production, their mode of actions group, application rate per acre and per season, and reentry interval. It also discusses the performance of these herbicides on several weeds under Florida conditions. Written by J. A. Ferrell, G. E. MacDonald, and P. Devkota, and published by the UF/IFAS Agronomy Department, revised May 2020.

Seasonal Nonstructural Carbohydrate Patterns in Dewberry (Rubus spp.) Roots

Weed Science ◽  
2021 ◽  
pp. 1-23
Author(s):  
Katherine M. Ghantous ◽  
Hilary A. Sandler
Keyword(s):  
Weed Management ◽  
Management Practices ◽  
Soluble Sugars ◽  
Leaf Expansion ◽  
Control Measures ◽  
Growth Stages ◽  
Phenological Stages ◽  
Long Term Storage ◽  
Nonstructural Carbohydrate ◽  
Fruit Maturity

Abstract Applying control measures when carbohydrate levels are low can decrease the likelihood of plant survival, but little is known about the carbohydrate cycles of dewberry (Rubus spp.), a problematic weed group on cranberry farms. Weedy Rubus plants were collected from areas adjacent to production beds on commercial cranberry farms in Massachusetts, two locations per year for two years. For each site and year, four entire plants were collected at five phenological stages: budbreak, full leaf expansion, flowering, fruit maturity, and after onset of dormancy. Root sections were analyzed for total nonstructural carbohydrate (TNC; starch, sucrose, fructose, and glucose). Overall trends for all sites and years showed TNC were lowest at full leaf expansion or flowering; when sampled at dormancy, TNC concentrations were greater than or equal to those measured at budbreak. Starch, a carbohydrate form associated with long-term storage, had low levels at budbreak, leaf expansion and/or flowering with a significant increase at fruit maturity and the onset of dormancy, ending at levels higher than those found at budbreak. The concentration of soluble sugars, carbohydrate forms readily usable by plants, was highest at budbreak compared to the other four phenological samplings. Overall, our findings supported the hypothesis that TNC levels within the roots of weedy Rubus plants can be predicted based on different phenological growth stages in Massachusetts. However, recommendations for timing management practices cannot be based on TNC cycles alone; other factors such as temporal proximity to dormancy may also impact Rubus plants recovery and further research is warranted. Late-season damage should allow less time for plants to replenish carbohydrate reserves (prior to the onset of dormancy), thereby likely enhancing weed management tactics effectiveness over time. Future studies should consider tracking the relationship between environmental conditions, phenological stages, and carbohydrate trends.

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