Abstract: One of the most damaging species in sunflower crops in Brazil is the hairy beggarticks (Bidens pilosa L.). The large number of seeds, the various vegetative cycles during the year, the staggered germination and the scarcity of selective and effective herbicides to control this weed in sunflower are some of attributes that hinder the effectiveness in controlling hairy beggarticks populations. The experiment was carried out with the objectives of evaluating the control of hairy beggarticks plants in sunflower crops, and to assess sunflower tolerance to residual herbicides. The treatments were as follows: S-metolachlor (1,200 and 2,400 g ai ha-1), flumioxazin (60 and 120 g ai ha-1), sulfentrazone (150 and 300 g ai ha-1) and two controls (weedy and weed-free check). Phytotoxicity on sunflower plants, percentage of control and density of hairy beggarticks plants, sunflower stand and plant height, head diameter, oil content and sunflower yield were evaluated. The herbicides flumioxazin and sulfentrazone were the most efficient in hairy beggarticks control. S-metolachlor provided acceptable control levels. S-metolachlor (1,200 g ha-1), flumioxazin (60 g ha-1) and sulfentrazone (150 g ha-1) were the most selective doses for sunflower crop.
Abstract: The experiment was carried out in Valença, Rio de Janeiro State, Brazil, to evaluate the selectivity and weed control of carotenoid biosynthesis inhibiting herbicides applied alone or in combination with atrazine in elephant grass crop. The treatments were as follows: mesotrione (0.072 and 0.144 kg ha-1 + 0.5% v/v mineral oil - Assist®), tembotrione (0.075 and 0.100 kg ha-1 + 0.5% v/v mineral oil - Aureo®), atrazine + mesotrione (1.25 + 0.072 kg ha-1 + 0.5% v/v mineral oil - Assist®), atrazine + tembotrione (1.25 + 0.100 kg ha-1 + 0.5% v/v mineral oil - Aureo®), atrazine + mesotrione (1.25 + 0.072 kg ha-1), atrazine + tembotrione (1.25 + 0.100 kg ha-1) and two controls (hoed and unhoed check). Two application rates of mesotrione with the addition of mineral oil or the tank mixture of atrazine plus mesotrione, with or without the addition of mineral oil, did not provide injuries capable to reduce elephant grass forage yield. Tembotrione was phytotoxic to elephant grass when applied with mineral oil. Atrazine and tembotrione in a tank-mix, with or without mineral oil, were also phytotoxic to elephant grass. All treatments provided satisfactory weed control.
Abstract: For the past three years, the Danish project,
RoboWeedSupport, has sought to bridge the gap between the potential
herbicide savings using a decision support system and the required
weed inspections. In order to automate the weed inspections it is
desired to generate a map of the weed species present within the
field, to generate the map images must be captured with samples
covering the field. This paper investigates the economical cost of
performing this data collection based on a camera system mounted
on a all-terain vehicle (ATV) able to drive and collect data at up to 50
km/h while still maintaining a image quality sufficient for identifying
newly emerged grass weeds. The economical estimates are based on
approximately 100 hectares recorded at three different locations in
Denmark. With an average image density of 99 images per hectare
the ATV had an capacity of 28 ha per hour, which is estimated to cost
6.6 EUR/ha. Alternatively relying on a boom solution for an existing
tracktor it was estimated that a cost of 2.4 EUR/ha is obtainable under
equal conditions.
Abstract: Present paper enumerates highlights of seasonal
variation in floristic composition and ecological strategies for the
management of ‘Gujar Tal’ at Jaunpur in tropical semi-arid region of
eastern U.P. (India). Total composition of macrophytes recorded was
47 from 26 families with maximum 6 plant species of Cyperaceae
from April, 2012 to March, 2013 at certain periodic intervals.
Maximum number of plants (39) was present during winter followed
by (37) rainy and (27) summer seasons. The distribution pattern
depicted that maximum number of plants (27) was of marshy and
swampy habitats usually transitional between land and water.
Abstract: Diminished antioxidant defense or increased
production of reactive oxygen species in the biological system can
result in oxidative stress which may lead to various
neurodegenerative diseases including Alzheimer’s disease (AD).
Microglial activation also contributes to the progression of AD by
producing several proinflammatory cytokines, nitric oxide (NO) and
prostaglandin E2 (PGE2). Oxidative stress and inflammation have
been reported to be possible pathophysiological mechanisms
underlying AD. In addition, the cholinergic hypothesis postulates that
memory impairment in patient with AD is also associated with the
deficit of cholinergic function in the brain. Although a number of
drugs have been approved for the treatment of AD, most of these
synthetic drugs have diverse side effects and yield relatively modest
benefits. Marine algae have great potential in pharmaceutical and
biomedical applications as they are valuable sources of bioactive
properties such as anticoagulation, antimicrobial, antioxidative,
anticancer and anti-inflammatory. Hence, this study aimed to provide
an overview of the properties of Malaysian seaweeds (Padina
australis, Sargassum polycystum and Caulerpa racemosa) in
inhibiting oxidative stress, neuroinflammation and cholinesterase
enzymes. These seaweeds significantly exhibited potent DPPH and
moderate superoxide anion radical scavenging ability (P
Abstract: Weed suppression and weeding are necessary measures
for rice cultivation. Weed suppression precedes the process of
weeding. It means suppressing the growth of young weeds and
creating a weed-less environment. If we suppress the growth of weeds,
we can reduce the number of weeds in a paddy field. This would result
in a reduction of the weeding work load.
In this paper, we will show how we developed a weed suppression
robot for the purpose of reducing the weeding work load. The robot
has a laser range finder for autonomous mobility and a robot arm for
weed suppression. It travels along the rice rows without stepping on
and injuring the rice plants in a paddy field. The robot arm applies
force to the weed seedlings and thereby suppresses the growth of
weeds. This paper will explain the methodology of the autonomous
mobile, the experiment in weed suppression, and the method of
controlling the robot’s posture on uneven ground.
Abstract: The effect of tillage technology of maize on intensity of weed infestation and weed species composition was observed at experimental field. Maize is grown consecutively since 2001. The experimental site is situated at an altitude of 230 m above sea level in the Czech Republic. Variants of tillage technology are CT: plowing – conventional tillage 0.22 m, MT: loosening – disc tillage on the depth of 0.1 – 0.12 m, NT: direct sowing – without tillage. The evaluation of weed infestation was carried out by numerical method in years 2012 and 2013. Within the monitoring were found 20 various species of weeds. Conventional tillage (CT) primarily supports the occurrence of perennial weeds (Cirsium arvense, Convolvulus arvensis). Late spring species (Chenopodium album, Echinochloa crus-galli) were more frequently noticed on variants of loosening (MT) and direct sowing (NT). Different tillage causes a significant change of weed species spectrum in maize.
Abstract: The present study aimed to investigate the effect of two type of soil (clay and sandy soils) in the potential allelopathic effects of Artemisia herba-alba, Oudneya africana crude powder (0, 1, 3 and 6%) on some growth parameters of two weeds (Bromus tectorum and Melilotus indica) under laboratory conditions (pot experiment).
The experimental findings have reported that the donor species crude powder concentrations were suppressing to shoot length (SL), root length (RL) and the leaf number (LN)) in both soil types and caused a gradual reduction particularly when they are high. However, the reduction degree was varied and species, concentration dependent. The suppressive effect of the two donors on the two weedy species was in the following order Melilotus indica > Bromus tectorum. Generally, the growth parameters of two recipient species were significantly decreased with the increase of each of the donor species crude powder concentration levels. Concerning the type of soil stoical analyses indicated that significant difference between clay and sandy soils.
Abstract: Information on weed distribution within the field is
necessary to implement spatially variable herbicide application.
Since hand labor is costly, an automated weed control system could be
feasible. This paper deals with the development of an algorithm for
real time specific weed recognition system based on Histogram
Analysis of an image that is used for the weed classification. This
algorithm is specifically developed to classify images into broad and
narrow class for real-time selective herbicide application. The
developed system has been tested on weeds in the lab, which have
shown that the system to be very effectiveness in weed identification.
Further the results show a very reliable performance on images of
weeds taken under varying field conditions. The analysis of the results
shows over 95 percent classification accuracy over 140 sample images
(broad and narrow) with 70 samples from each category of weeds.
Abstract: The identification and classification of weeds are of
major technical and economical importance in the agricultural
industry. To automate these activities, like in shape, color and
texture, weed control system is feasible. The goal of this paper is to
build a real-time, machine vision weed control system that can detect
weed locations. In order to accomplish this objective, a real-time
robotic system is developed to identify and locate outdoor plants
using machine vision technology and pattern recognition. The
algorithm is developed to classify images into broad and narrow class
for real-time selective herbicide application. The developed
algorithm has been tested on weeds at various locations, which have
shown that the algorithm to be very effectiveness in weed
identification. Further the results show a very reliable performance
on weeds under varying field conditions. The analysis of the results
shows over 90 percent classification accuracy over 140 sample
images (broad and narrow) with 70 samples from each category of
weeds.
Abstract: The spatial variation in plant species associated with intercropping is intended to reduce resource competition between species and increase yield potential. A field experiment was carried out on corn (Zea mays L.) and soybean (Glycine max L.) intercropping in a replacement series experiment with weed contamination consist of: weed free, infestation of redroot pigweed, infestation of jimsonweed and simultaneous infestation of redroot pigweed and jimsonweed in Karaj, Iran during 2007 growing season. The experimental design was a randomized complete block in factorial experiment with replicated thrice. Significant (P≤0.05) differences were observed in yield in intercropping. Corn yield was higher in intercropping, but soybean yield was significantly reduced by corn when intercropped. However, total productivity and land use efficiency were high under the intercropping system even in contamination of either species of weeds. Aggressivity of corn relative to soybean revealed the greater competitive ability of corn than soybean. Land equivalent ratio (LER) more than 1 in all treatments attributed to intercropping advantages and was highest in 50: 50 (corn/soybean) in weed free. These findings suggest that intercropping corn and soybean increase total productivity per unit area and improve land use efficiency. Considering the experimental findings, corn-soybean intercropping (50:50) may be recommended for yield advantage, more efficient utilization of resources, and weed suppression as a biological control.
Abstract: One important objective in Precision Agriculture is to minimize the volume of herbicides that are applied to the fields through the use of site-specific weed management systems. In order to reach this goal, two major factors need to be considered: 1) the similar spectral signature, shape and texture between weeds and crops; 2) the irregular distribution of the weeds within the crop's field. This paper outlines an automatic computer vision system for the detection and differential spraying of Avena sterilis, a noxious weed growing in cereal crops. The proposed system involves two processes: image segmentation and decision making. Image segmentation combines basic suitable image processing techniques in order to extract cells from the image as the low level units. Each cell is described by two area-based attributes measuring the relations among the crops and the weeds. From these attributes, a hybrid decision making approach determines if a cell must be or not sprayed. The hybrid approach uses the Support Vector Machines and the Fuzzy k-Means methods, combined through the fuzzy aggregation theory. This makes the main finding of this paper. The method performance is compared against other available strategies.
Abstract: Texture classification is a trendy and a catchy
technology in the field of texture analysis. Textures, the repeated
patterns, have different frequency components along different
orientations. Our work is based on Texture Classification and its
applications. It finds its applications in various fields like Medical
Image Classification, Computer Vision, Remote Sensing,
Agricultural Field, and Textile Industry. Weed control has a major
effect on agriculture. A large amount of herbicide has been used for
controlling weeds in agriculture fields, lawns, golf courses, sport
fields, etc. Random spraying of herbicides does not meet the exact
requirement of the field. Certain areas in field have more weed
patches than estimated. So, we need a visual system that can
discriminate weeds from the field image which will reduce or even
eliminate the amount of herbicide used. This would allow farmers to
not use any herbicides or only apply them where they are needed. A
machine vision precision automated weed control system could
reduce the usage of chemicals in crop fields. In this paper, an
intelligent system for automatic weeding strategy Multi Resolution
Combined Statistical & spatial Frequency is used to discriminate the
weeds from the crops and to classify them as narrow, little and broad
weeds.
Abstract: Information on weed distribution within the field is necessary to implement spatially variable herbicide application. Since hand labor is costly, an automated weed control system could be feasible. This paper deals with the development of an algorithm for real time specific weed recognition system based on Histogram Maxima with threshold of an image that is used for the weed classification. This algorithm is specifically developed to classify images into broad and narrow class for real-time selective herbicide application. The developed system has been tested on weeds in the lab, which have shown that the system to be very effectiveness in weed identification. Further the results show a very reliable performance on images of weeds taken under varying field conditions. The analysis of the results shows over 95 percent classification accuracy over 140 sample images (broad and narrow) with 70 samples from each category of weeds.