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Ortiz, B.V
Zhou, J
Zhang , Z
Zhao, C
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Authors
Zhao, C
Zhou, J
Deng, W
Yang, X
Sun, C
Qian, J
Ji, Z
Qiao, S
Chen, M
Zhao, C
Li, M
Fu, W
Meng, Z
Wu, G
Dong, J
Mei, H
Zhao, C
Song, X
Zhao, C
Chen, L
Huang, W
Cui, B
Ortiz, B.V
Vellidis, G
Balkcom, K
Stone, H
Fulton, J.P
vanSanten, E
Torino, M.S
Ortiz, B.V
Fulton, J.P
Balkcom, K
Chen, L
Zhao, C
Huang, W
Chen, T
Wang , J
Huang, W
Zhao, C
Ma, W
Zhao, C
Zaman, Q.U
Zach, D
Fulton, J.P
Balkcom, K.S
Ortiz, B.V
McDonald, T.P
Pate, G.L
Virk, S.S
Poncet, A
Zhao, C
Li, B
Zhao, C
Wu, G
Meng, Z
Fu, W
Li, L
Wei, X
Khot, L
Zhou, J
Boydston, R
Miklas, P.N
Porter, L
Zhou, J
Sudduth, K.A
Feng, A
Zhou, J
Xu, Z
Zhou, J
Zhou, J
Ortiz, B.V
Lena, B.P
Morlin , F
Morata, G
Duarte de Val, M
Prasad, R
Gamble, A
Ransom, C.J
Vong, C
Veum, K.S
Sudduth, K.A
Kitchen, N.R
Zhou, J
Das, A
Flores, P
Zhang , Z
Friskop, A
Mathew, J
Mathew, J.J
Flores, P.J
Stenger, J
Miranda, C
Zhang, Z
Das, A.K
Lee, K
Sudduth, K.A
Zhou, J
Topics
Precision Crop Protection
Engineering Technologies and Advances
Spatial Variability in Crop, Soil and Natural Resources
Guidance, Robotics, Automation, and GPS Systems
Sensor Application in Managing In-season Crop Variability
Modeling and Geo-statistics
Remote Sensing Applications in Precision Agriculture
Precision Horticulture
Engineering Technologies and Advances
Spatial Variability in Crop, Soil and Natural Resources
Engineering Technologies and Advances
Unmanned Aerial Systems
Applications of Unmanned Aerial Systems
Farm Animals Health and Welfare Monitoring
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Drainage Optimization and Variable Rate Irrigation
Applications of Unmanned Aerial Systems
Precision Agriculture and Global Food Security
Type
Poster
Oral
Year
2012
2010
2014
2016
2018
2022
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Authors

Filter results21 paper(s) found.

1. Application Of Algebra Hyper-curve Neural Network In Soil Nutrient Spatial Interpolation

Study on spatial variability of soil nutrient is the basis of soil nutrient management in precision agriculture. For study on application potential and characteristics of algebra hyper-curve neural network(AHNN) in delineating soil properties spatial variability and interpolation, total 956 soil samples were taken for alkaline hydrolytic nitrogen measurement from a 50 hectares field using 20m*20m grid sampling. The test data set consisted of 100 random samples extracting... L. Chen, C. Zhao, W. Huang, T. Chen, J. Wang

2. Inversion Of Vertical Distribution Of Chlorophyll Concentration By Canopy Reflectance Spectrum In Winter Wheat

          The objective of this study was to investigate the inversion of foliage chlorophyll concentration(Chl) vertical-layer distribution by bidirectional reflectance difference function (BRDF) data, so as to provide guidance on the application of fertilizer. The ratio of transformed chlorophyll absorption reflectance index (TCARI) to optimized soil adjusted vegetation index (OSAVI) was named as canopy chlorophyll inversion index (CCII) in... W. Huang, C. Zhao

3. Design And Experiment On Target Spraying Robot For Greenhouse

In greenhouse, the robot sprayers give rise to concern as they  reduce the labor intensity and improve the accuracy of  the spraying. This paper details the progress to date in the development of a precision robot sprayer. The precision robot sprayer is able to adjust both liquid and air volume to match, the branches contour and location of the greenhouse crops with two ultrasonic sensors  which ensures the position of the plants in the greenhouse. The spraying robot with the... W. Ma, C. Zhao, Q.U. Zaman, D. Zach

4. Comparison and Evaluation of Spray Characteristics of Three Types of Variable-Rate Spray

For the present developing direction of "low-input sustainable agriculture", variable-rate technology is increasingly concerned in agricultural engineering field. The technology of variable-rate precision chemical application is the typical of variable-rate technology. In China, agro-chemical production technology has reached the international advanced level, but the chemical application... C. Zhao, J. Zhou, W. Deng

5. Modeling and Decision Support System for Precision Cucumber Protection in Greenhouses

The plant disease... X. Yang, C. Sun, J. Qian, Z. Ji, S. Qiao, M. Chen, C. Zhao, M. Li

6. Study on Monitoring System of Wheat Sowing

       In order to real-time monitoring the sowing status of the multi-channel seeder, a distributed monitoring system is developed. The monitoring module of sowing and the monitoring terminal is designed with ... W. Fu, Z. Meng, G. Wu, J. Dong, H. Mei, C. Zhao

7. Winter Wheat Growth Uniformity Monitoring Through Remote Sensed Images

  ... X. Song, C. Zhao, L. Chen, W. Huang, B. Cui

8. Evaluation of The Advantages of Using GPS-Based Auto-Guidance on Rolling Terrain Peanut Fields

  ... B.V. Ortiz, G. Vellidis, K. Balkcom, H. Stone, J. Fulton, E. Vansanten

9. Evaluation of Differences in Corn Biomass and Nitrogen Uptake at Various Growth Stages Using Spectral Vegetation Indices

Application of canopy sensors for nitrogen (N) fertilizer management for corn grain production in the Southeast US requires... M.S. Torino, B.V. Ortiz, J. Fulton, K. Balkcom

10. Row-Crop Planter Requirements To Support Variable-Rate Seeding Of Maize

Current planting technology possesses the ability to increase crop productivity and improve field efficiency by precisely metering and placing crop seeds. Growing high yielding crops not only requires using the right seed variety and rate but also achieving optimal performance with available planter technology. Planter performance depends on using the correct planter and technology (display and rate controller system) setup which consists of determining optimal settings for different planting... J.P. Fulton, K.S. Balkcom, B.V. Ortiz, T.P. Mcdonald, G.L. Pate, S.S. Virk, A. Poncet

11. Heavy Metal PB2+ Pollution Detection In Soil Using Terahertz Time-domain Spectroscopy For Precision Agriculture

Soil is an important natural resource for human beings. With the rapid development of modern industry, heavy metals pollution in soil has made prominent influences on farmland environment. It was reported that, one fifth of China's cultivated lands and more than 217,000 farms in the US have been polluted at different levels by heavy metals. The crop grows in the polluted soil and the heavy metal ions transfer from soil to the plant and agro-products. As a result, the crop yield... C. Zhao, B. Li

12. The Device of Air-assisted Side Deep Precision Fertilization for Rice Transplanter

Rice is the most important crop in China, which has the largest plant area. Fertilization is an important process of rice production, which directly affects the yield of crops, reasonable and effective use of chemical fertilizer can improve the yield of crops. At present, the mechanization level of rice fertilization is very low in China, and the artificial fertilization requires a large amount of fertilizer which caused the uneven distribution. The rice side deep fertilizing is an ideal way of... C. Zhao, G. Wu, Z. Meng, W. Fu, L. Li, X. Wei

13. Small UAS Integrated Sensing Tools for Abiotic Stress Monitoring in Irrigated Pinto Beans

Precision agriculture is a practical approach to maximize crop yield with optimal use of rapidly depleting natural resources. Availability of specific and high resolution crop data at critical growth stages is a key for real-time data driven decision support for precision agriculture management during the production season. The goal of this study was to evaluate the feasibility of using small unmanned aerial system (UAS) integrated remote sensing tools to monitor the abiotic stress of eight irrigated... L. Khot, J. Zhou, R. Boydston, P.N. Miklas, L. Porter

14. Monitoring Soybean Growth and Yield Due to Topographic Variation Using UAV-Based Remote Sensing

Remote sensing has been used as an important tool in precision agriculture. With the development of unmanned aerial vehicle (UAV) technology, collection of high-resolution site-specific field data becomes promising. Field topography affects spatial variation in soil organic carbon, nitrogen and water content, which ultimately affect crop performance. To improve crop production and reduce inputs to the field, it is critical to collect site-specific information in a real-time manner and at a large... J. Zhou, K.A. Sudduth, A. Feng

15. Detect Estrus in Sows Using a Lidar Sensor and Machine Learning

Accurate estrus detection of sows is labor intensive and is crucial to achieve high farrowing rate. This study aims to develop a method to detect accurate estrus time by monitoring the change in vulvar swollenness around estrus using a light detection and ranging (LiDAR) camera. The measurement accuracy of the LiDAR camera was evaluated in laboratory conditions before it was used in monitoring sows in a swine research facility. In this study, twelve multiparous individually housed sows were continuously... J. Zhou, Z. Xu

16. Toward Smart Soybean Variety Selection Using UAV-based Imagery and Machine Learning

The efficiency of crop breeding programs is evaluated by the genetic gain of a primary trait of interest, e.g., yield and resilience to stress, achieved in one year through artificial selection of advanced breeding materials. Conventional breeding programs select superior genotypes using the primary trait (yield) based on combine harvesters, which is labor-intensive and often unfeasible for single-row progeny trials due to their large population, complex genetic behavior, and high genotype-environment... J. Zhou, J. Zhou

17. Can Topographic Indices Be Used for Irrigation Management Zone Delineation

Soil water movement is affected by soil physical properties and field terrain changes. The identification of within-field areas prone to excess or deficit of soil moisture could support the implementation of variable rate irrigation and adoption of irrigation scheduling strategies. This study evaluated the use of the topographic wetness index (TWI) and topographic position index (TPI) to understand and explain within-field soil moisture variability. Volumetric water content (VWC) collected in... B.V. Ortiz, B.P. Lena, F. morlin , G. Morata, M. Duarte de val, R. Prasad, A. Gamble

18. Estimating Soil Carbon Stocks with In-field Visible and Near-infrared Spectroscopy

Agricultural lands can be a sink for carbon and play an important role in offsetting carbon emissions. Current methods of measuring carbon sequestration—through repeated temporal soil samples—are costly and laborious. A promising alternative is using visible, near-infrared (VNIR) diffuse reflectance spectroscopy. However, VNIR data are complex, which requires several data processing steps and often yields inconsistent results, especially when using in situ VNIR measurements. Using... C.J. Ransom, C. Vong, K.S. Veum, K.A. Sudduth, N.R. Kitchen, J. Zhou

19. Assessment of Goss Wilt Disease Severity Using Machine Learning Techniques Coupled with UAV Imagery

Goss Wilt has become a common disease in corn fields in North Dakota.  It has been one of the most yield-limiting diseases, causing losses of up to 50%. The current method to identify the disease is through visual inspection of the field, which is inefficient, and can be subjective, with misleading results, due to evaluator fatigue. Therefore, developing a reliable, accurate, and automated tool for assessing the severity of Goss's Wilt disease has become a top priority. The use of unmanned... A. Das, P. Flores, Z. Zhang , A. Friskop, J. Mathew

20. Comparative Analysis of Light-weight Deep Learning Architectures for Soybean Yield Estimation Based on Pod Count from Proximal Sensing Data for Mobile and Embedded Vision Applications

Crop yield prediction is an important aspect of farming and food-production. Therefore, estimating yield is important for crop breeders, seed-companies, and farmers to make informed real-time financial decisions. In-field soybean (Glycine max L.(Merr.)) yield estimation can be of great value to plant breeders as they screen thousands of plots to identify better yielding genotypes that ultimately will strengthen national food security. Existing soybean yield estimation tools,... J.J. Mathew, P.J. Flores, J. Stenger, C. Miranda, Z. Zhang, A.K. Das

21. Hay Yield Estimation Using UAV-based Imagery and a Convolutional Neural Network

Yield monitoring systems are widely used commercially in grain crops to map yields at a scale of a few meters. However, such high-resolution yield monitoring and mapping for hay and forage crops has not been commercialized. Most commercial hay yield monitoring systems only obtain the weight of individual bales, making it difficult to map and understand the spatial variability in hay yield. This study investigated the feasibility of an unmanned aerial vehicle (UAV)-based remote sensing system for... K. Lee, K.A. Sudduth, J. Zhou