scholarly journals A Tactile Method for Rice Plant Recognition Based on Machine Learning

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5135
Author(s):  
Xueshen Chen ◽  
Yuanyang Mao ◽  
Xu Ma ◽  
Long Qi
Keyword(s):  
Rice Plant ◽  
Tactile Sensor ◽  
Box Dimension ◽  
Neural Network Classifier ◽  
Tactile Information ◽  
Rice Plants ◽  
Vibration Data ◽  
Plant Recognition ◽  
Physical Touch ◽  
Rice Leaves

Accurate and real-time recognition of rice plants is the premise underlying the implementation of precise weed control. However, achieving desired results in paddy fields using the traditional visual method is difficult due to the occlusion of rice leaves and the interference of weeds. The objective of this study was to develop a novel rice plant recognition sensor based on a tactile method which acquires tactile information through physical touch. The tactile sensor would be mounted on the paddy field weeder to provide identification information for the actuator. First, a flexible gasbag filled with air was developed, where vibration features produced by tactile and sliding feedback were acquired when this apparatus touched rice plants or weeds, allowing the subtle vibration data with identification features to be reflected through the voltage value of an air-pressured sensor mounted inside the gasbag. Second, voltage data were preprocessed by three algorithms to optimize recognition features, including dimensional feature, dimensionless feature, and fractal dimension. The three types of features were used to train and test a neural network classifier. To maximize classification accuracy, an optimum set of features (b (variance), f (kurtosis), h (waveform factor), l (box dimension), and m (Hurst exponent)) were selected using a genetic algorithm. Finally, the feature-optimized classifier was trained, and the actual performances of the sensor at different contact positions were tested. Experimental results showed that the recognition rates of the end, middle, and root of the sensor were 90.67%, 98%, and 96% respectively. A tactile-based method with intelligence could produce high accuracy for rice plant recognition, as demonstrated in this study.

scholarly journals Hi-Speed Tactile Sensing for Array-type Tactile Sensor and Object Manipulation based on Tactile Information

2012 ◽  
Vol 25 (5) ◽  
pp. 117-125
Author(s):  
Wataru Fukui ◽  
Futoshi Kobayashi ◽  
Fumio Kojima ◽  
Hiroyuki Nakamoto ◽  
Tadashi Maeda ◽  
...  
Keyword(s):  
Tactile Sensor ◽  
Object Manipulation ◽  
Tactile Sensing ◽  
Tactile Information ◽  
Array Type

Effects of Herbicides on Diseases of Rice (Oryza sativa)

Weed Science ◽  
1977 ◽  
Vol 25 (5) ◽  
pp. 441-447 ◽  
Author(s):  
E. Inderawati ◽  
R. Heitefuss
Keyword(s):  
Oryza Sativa ◽  
Disease Severity ◽  
Culture Media ◽  
Direct Action ◽  
Culture Method ◽  
Xanthomonas Oryzae ◽  
Commercial Formulation ◽  
Rice Plants ◽  
Agar Media ◽  
Rice Leaves

Seven herbicides were tested for their effect on growth of Pyricularia oryzae Cavara, Hypochnus sasakii Shirai, and Xanthomonas oryzae Uyeda & Ishiyama Dowson on agar media and for subsequent influence on disease intensity on rice plants (Oryza sativa L.) in the greenhouse. The herbicides studied were: propanil 3′,4′-dichloro-propionanilide), NTN 5$006 [O-(2-nitro-4-methylphenyl)-O-ethyl-N-isopropyl-phosphor-amidothioate], simetryn [2,4-bis(ethylamino)-6-)methylthio)-s-triazine], terbutryn [2-(tert-butylamino)-4-(ethylamino)-6-(methylthio)-s-triazine], nitrofen (2,4-dichlorophenyl-p-nitrophenyl ether), molinate (S-ethyl hexahydro-1H-azepine-1-carbothioate), and aglypt (4-amino-3-methylthio-6-phenyl-1,2,4-triazine-5-on). The growth of P. oryzae, H. sasakii and X. oryzae on culture media containing 10 μg/ml commercial formulation of propanil was reduced to approximately 50% of the control. The other herbicides tested were less effective. Differences in disease severity produced on rice plants treated with the previously mentioned herbicides were in agreement with the results obtained by the culture method. The effect of simetryn and nitrofen on disease severity was stronger than expected from the small direct action on the pathogen in culture. It is suggested that the influence of these two compounds on the disease intensity is due to their effect on the host plant rather than the pathogen directly. Propanil was effective only if applied immediately or up to 1 day before inoculation, indicating that this herbicide is degraded on or within the rice leaves.

scholarly journals Magnetostrictive tactile sensor of detecting friction and normal force for object recognition

2020 ◽  
Vol 17 (4) ◽  
pp. 172988142093232
Author(s):  
Bing Zhang ◽  
Bowen Wang ◽  
Yunkai Li ◽  
Shaowei Jin
Keyword(s):  
Recognition Rate ◽  
Tactile Sensor ◽  
Tactile Sensing ◽  
Dynamic Force ◽  
Force Output ◽  
Tactile Sensors ◽  
Tactile Information ◽  
Normal Contact ◽  
New Type ◽  
Learning Machine

Tactile information is valuable in determining properties of objects that are inaccessible from visual perception. A new type of tangential friction and normal contact force magnetostrictive tactile sensor was developed based on the inverse magnetostrictive effect, and the force output model has been established. It can measure the exerted force in the range of 0–4 N, and it has a good response to the dynamic force in cycles of 0.25–0.5 s. We present a tactile perception strategy that a manipulator with tactile sensors in its grippers manipulates an object to measure a set of tactile features. It shows that tactile sensing system can use these features and the extreme learning machine algorithm to recognize household objects—purely from tactile sensing—from a small training set. The complex matrixes show the recognition rate is up to 83%.

Detecting Feature of Haptic Interaction Based on Distributed Tactile Sensor Network on Whole Body

2007 ◽  
Vol 19 (1) ◽  
pp. 42-51 ◽  
Author(s):  
Tomoyuki Noda ◽  
◽  
Takahiro Miyashita ◽  
Hiroshi Ishiguro ◽  
Kiyoshi Kogure ◽  
...  
Keyword(s):  
Sensor Network ◽  
Tactile Sensor ◽  
The Self ◽  
Whole Body ◽  
Transmission Protocol ◽  
Processing Unit ◽  
Haptic Interaction ◽  
Tactile Information ◽  
Self Organized ◽  
Basic Experiments

To extract information about users contacting robots physically, the distribution density of tactile sensor elements, the sampling rate, and the resolution all must be high, increasing the volume of tactile information. In the self-organized skin sensor network we propose for dealing with a large number of tactile sensors embedded throughout a humanoid robot, each network node having a processing unit is connected to tactile sensor elements and other nodes. By processing tactile information in the network based on the situation, individual nodes process and reduce information rapidly in high sampling. They also secure information transmission routes to the host PC using a data transmission protocol for self-organizing sensor networks. In this paper, we verify effectiveness of our proposal through sensor network emulation and basic experiments in spatiotemporal calculation of tactile information using prototype hardware. As an emulation result of the self-organized sensor network, routes to the host PC are secured at each node, and a tree-like network is constructed recursively with the node as a root. As the basic experiments, we describe an edge detection as data processing and extraction for haptic interaction. In conclusion, local information processing is effective for detecting features of haptic interaction.

Changes in release level of momilactone B into the environment from rice throughout its life cycle

2003 ◽  
Vol 30 (9) ◽  
pp. 995 ◽  
Author(s):  
Hisashi Kato-Noguchi ◽  
Takeshi Ino ◽  
Masahiko Ichii
Keyword(s):  
Life Cycle ◽  
Release Rate ◽  
Rice Plant ◽  
Growth Inhibitor ◽  
Rice Plants ◽  
Flowering Initiation ◽  
Single Rice ◽  
Germination And Growth

Momilactone B was released into the neighboring environment from rice throughout its life cycle. The rate of momilactone B release from rice increased until flowering initiation, and then decreased. The release rate of momilactone B at the day of flowering started was 2.1 μg plant–1 d–1. On average, a single rice plant released about 100 μg of momilactone B into the neighboring environment over its life cycle. Since momilactone B is a growth inhibitor, these results suggest that momilactone B released from rice plants may serve as an allelochemical to inhibit the germination and growth of neighboring plants.

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