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Kashetri, S
Wan Ismail, W
Ketterings, Q
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Authors
Wan Ismail, W
Abdul Rahman, K
Upadhyaya, P
Karkee, M
Zhang, X
Kashetri, S
Marcaida, M
Zhang, X
Srinivasagan, S
Shajahan, S
Ketterings, Q
Srinivasagan, S
Ketterings, Q
Marcaida, M
Shajahan, S
Ramos-Tanchez, J
Cho, J
Thompson, L
Guinness, J
Goel, R
Topics
Spatial and Temporal Variability in Crop, Soil and Natural Resources
Big Data, Data Mining and Deep Learning
Data Analytics for Production Ag
Drivers and Barriers to Adoption of Precision Ag Technologies or Digital Agriculture
Type
Oral
Year
2008
2022
2024
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1. Development of Real-time Color Analysis for the On- Line Automated Weeding Operations

Weeds compete with the crop for water, light, nutrients and space, and therefore reduce crop yields and also affect the efficient use of machinery. Chemical sprayer is the most popular method to eradicate weeds but has cause hazardous to the environment, crops and workers. A smart sprayer is required to control the usage of chemical weedicides at the optimal level. Thus an on-line automated sprayer is introduced to the Malaysian farmers to locate in the real time environment the existence and... W. Wan ismail, K. Abdul rahman

2. Automated Lag Phase Detection in Wine Grapes

Crop yield estimation, an important managerial tool for vineyard managers, plays a crucial role in planning pre/post-harvest operations to achieve desired yield and improve efficiency of various field operations. Although various technological approaches have been developed in the past for automated yield estimation in wine grapes, challenges such as cost and complexity of the technology, need of higher technical expertise for their operation and insufficient accuracy have caused major concerns... P. Upadhyaya, M. Karkee, X. Zhang, S. Kashetri

3. Can Soil Fertility Data and Topography Predict Yield Stability Zones for Corn Fields in New York?

Yield monitor systems play a vital role in precision agriculture given their ability to capture and map within-field yield variability. When three or more years of yield data are available, yield stability zone maps can be generated to show both the spatial and temporal variability of yield within a field. Based on the farm’s overall temporal mean and standard deviation for a specific crop, we can classify areas in the field as consistently high- (Q1) or low-yielding (Q4), and variably high-... M. Marcaida, X. Zhang, S. Srinivasagan, S. Shajahan, Q. Ketterings

4. Single-strip Spatial Evaluation Approach: a Simplified Method for Enhanced Sustainable Farm Management

On-farm experimentation (OFE) plays a pivotal role in evaluating and validating the effectiveness of agricultural practices and products. The results of OFE enable farmers to act and make changes that can enhance the farm’s economic and environmental sustainability. Experimental designs can be a barrier to the adoption of OFE. The conventional approach often involves randomized complete block designs with 3 to 5 replications in the field, which can be space-intensive and disrupt workflow... S. Srinivasagan, Q. Ketterings, M. Marcaida, S. Shajahan, J. Ramos-tanchez, J. Cho, , L. Thompson, J. Guinness, R. Goel