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Tian'en, C
Nazrul, F
Fritz, A
Shajahan, S
Frazier, R
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Authors
Burns, D
Overstreet, D
Kruse, D
Frazier, R
Blanche, D
Tian'en, C
Evers, B
Rekhi, M
Hettiarachchi, G
Welch, S
Fritz, A
Alderman, P.D
Poland, J
Jha, G
Nazrul, F
Nocco, M
Pagé Fortin, M
Whitaker, B
Diaz, D
Gal, A
Schmidt, R
Dey, 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
Nazrul, F
Kim, J
Dey, S
Palla, S
Sihi, D
Whitaker, B
Jha, G
Topics
Profitability, Sustainability and Adoption
Geospatial Data
Weather and Models for Precision Agriculture
Data Analytics for Production Ag
Drivers and Barriers to Adoption of Precision Ag Technologies or Digital Agriculture
Type
Poster
Oral
Year
2012
2022
2024
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Authors

Filter results7 paper(s) found.

1. On-Farm Trials Using Precision Ag in Northeast Louisiana

The availability of yield monitors and precision application equipment on producers’ farms have made it much easier for researchers to take the results from experiment station trials and apply them to producers’ fields.  Treatments/methods are applied in strips, by prescription, embedded plots or in combination.  Fields are divided into zones for analyzing the harvest yield data.  These can include soil type, soil Ec, or other criteria.  Treatments are analyzed... D. Burns, D. Overstreet, D. Kruse, R. Frazier, D. Blanche

2. Multi-objective Optimization Analysis Model for County Range Soil Nutrients Sampling Point Layout Based on Improved Genetic Algorithm

The layout of soil nutrients sampling points directly influence on the representative of soil samples and the precision of fertilization, also on sampling efficiency and sampling costs. By analyzing the various factors of county range farmland soil nutrients sampling, and setting the boundary conditions and objective function, the paper  established multi-objective optimization... C. Tian'en

3. Using On-the-Go Soil Sensors to Assess Spatial Variability within the KS Wheat Breeding Program

In plant breeding the impacts of genotype by environment interactions and the challenges to quantify these interactions has long been recognized. Both macro and microenvironment variations in precipitation, temperature and soil nutrient availability have been shown to impact breeder selections. Traditionally, breeders mitigate these interactions by evaluating genotype performance across varying environments over multiple years. However, limitations in labor, equipment and seed availably can limit... B. Evers, M. Rekhi, G. Hettiarachchi, S. Welch, A. Fritz, P.D. Alderman, J. Poland

4. Prediction of Field-scale Evapotranspiration Using Process Based Modeling and Geostatistical Time-series Interpolation

Irrigation scheduling depends on the combination of evaporative demand from the atmosphere, spatial and temporal heterogeneity in soil properties and changes in crop canopy during a growing season. This on-farm trial is based on data collected in 72-acre processing tomato field in Central Valley of California. The Multiband Spectrometric Arable Mark 2 sensors at three different locations in the field. Multispectral and thermal imagery provided by Ceres Imaging were collected eight times during... G. Jha, F. Nazrul, M. Nocco, M. Pagé fortin, B. Whitaker, D. Diaz, A. Gal, R. Schmidt

5. 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

6. 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

7. Machine Learning Algorithms in Detecting Long-term Effect of Climatic Factors for Alfalfa Production in Kansas

The water levels of the Ogallala Aquifer are depleting so much that agricultural land returns in Kansas are expected to drop by $34.1 million by 2050. It is imperative to understand how frequent droughts and the contrasting rates of groundwater withdrawal and recharge are affected by climate shifts in Kansas. Alfalfa, the ‘Queen of Forages’, is a water demanding crop which supplies high nutritional feed for beef industry that offered Kansas producers a $500 million production value... F. Nazrul, J. Kim, S. Dey, S. Palla, D. Sihi, B. Whitaker, G. Jha