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Hennessy, P.J
Harris, G
Guerrero, H.B
Watkins, K
Kim, J
Guerra, S.S
Kizer, E
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Authors
Marasca, I
Masiero, F.C
Fiorese, D.A
Guerra, S.S
Lancas, K.P
Kizer, E
Upadhyaya, S.K
Rojo, F
Ozmen, S
Ko-Madden, C
Zhang, Q
Becker, M
Velasquez, A.E
Guerrero, H.B
HIguti, V.A
Milori, D.M
Magalhães, D.V
Sung, N
Chung, S
Kim, Y
han, K
Choi, J
Kim, J
Cho, Y
Jang, S
Straw, C
Wyatt, B
Smith, A.P
Watkins, K
Hong, S
Floyd, W
Williams, D
Garza, C
Jansky, T
Hennessy, P.J
Esau, T.J
Schumann, A.W
Farooque, A.A
Zaman, Q.U
White, S.N
Tucker, M.W
Virk, S
Harris, G
Lessl, J
Levi, M
Topics
Spatial Variability in Crop, Soil and Natural Resources
Proximal Sensing in Precision Agriculture
Engineering Technologies and Advances
Geospatial Data
Big Data, Data Mining and Deep Learning
Site-Specific Nutrient, Lime and Seed Management
Type
Poster
Oral
Year
2014
2016
2022
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Filter results7 paper(s) found.

1. Spatial Dependence Of Soil Compaction In Annual Cycle Of Different Culture Of Cane Sugar For Sandy Soil

The Currently practiced mechanization for the production of sugar cane involves a heavy traffic of machinery and equipment. Studying the culture in its development environment generates a huge amount of information to fit the top managements and varieties for specific environments. The sugar cane cultivation has a heavy traffic of machinery and equipment, having more than 20 operations per cycle, and being more intense during harvest, providing increasing... I. Marasca, F.C. Masiero, D.A. Fiorese, S.S. Guerra, K.P. Lancas

2. Proximal Sensing of Leaf Temperature and Microclimatic Variables to Implement Precision Irrigation in Almond and Grape Crops

Irrigation decisions based on traditional soil moisture sensing often leads to uncertainty regarding the true amount of water available to the plant. Plant based sensing of water stress decreases this uncertainty. In specialty crops grown in California’s Central Valley, precision deficit irrigation based on plant water stress could be used to decrease water use and increase water use efficiency by supplying the necessary quantity of water only when it is needed by the plant. However, there... E. Kizer, S.K. Upadhyaya, F. Rojo, S. Ozmen, C. Ko-madden, Q. Zhang

3. Helvis - a Small-scale Agricultural Mobile Robot Prototype for Precision Agriculture

The use of agricultural robots is emerging in a complex scenario where it is necessary to produce more food to feed a crescent population, decrease production costs, fight plagues and diseases, and preserve nature. Around the world, there are many research institutes and companies trying to apply mobile robotics techniques in agricultural fields. Mostly, large prototypes are being used and their shapes and dimensions are very similar to tractors and trucks. In the present study, a small-scale... M. Becker, A.E. Velasquez, H.B. Guerrero, V.A. Higuti, D.M. Milori, D.V. Magalhães

4. Evaluation of a Sensor and Control Interface Module for Monitoring of Greenhouse Environment

Protected horticulture in greenhouses and plant factories has been increased in many countries due to the advantages of year-round production in controlled environment for improved productivity and quality. For protected horticulture, environmental conditions are monitored and controlled through wired and wireless devices. Various devices are used for monitoring and control of spatial and temporal variability in crop growth environmental conditions. Recently, various sensors and control devices,... N. Sung, S. Chung, Y. Kim, K. Han, J. Choi, J. Kim, Y. Cho, S. Jang

5. Investigating Spatial Relationship of Apparent Electrical Conductivity with Turfgrass and Soil Characteristics in Sand-capped Golf Course Fairways

Turfgrass quality decreases when grown on fine textured soils that are irrigated with poor quality water. As a result, sand-capping (i.e., a sand layer above existing native soil) is now considered during golf course fairway renovation and construction. Mapping spatial variability of soil apparent electrical conductivity (ECa) has recently been suggested to have applications for precision turfgrass management (PTM) in native soil fairways, but sand-capped fairways have received less... C. Straw, B. Wyatt, A.P. Smith, K. Watkins, S. Hong, W. Floyd, D. Williams, C. Garza, T. Jansky

6. Meta Deep Learning Using Minimal Training Images for Weed Classification in Wild Blueberry

Deep learning convolutional neural networks (CNNs) have gained popularity in recent years for their ability to classify images with high levels of accuracy. In agriculture, they have been applied for disease identification, crop growth monitoring, animal behaviour tracking, and weed classification. Datasets traditionally consisting of thousands of images of each desired target are required to train CNNs. A recent survey of Nova Scotia wild blueberry (Vaccinium angustifolium Ait.) fields,... P.J. Hennessy, T.J. Esau, A.W. Schumann, A.A. Farooque, Q.U. Zaman, S.N. White

7. Effectiveness of Different Precision Soil Sampling Strategies for Site-Specific Nutrient Management in Row-Crops

Soil sampling is an important component of site-specific nutrient management in precision agriculture. While precision soil sampling strategies such as grid or zone have been around for a while, the adoption and utilization of these strategies varies considerably among the growers, especially in the southeastern United States. The selection of an appropriate grid size or management zone further differ among the users depending on several factors. In order to better understand how some of the commonly... M.W. Tucker, S. Virk, G. Harris, J. Lessl, M. Levi