Proceedings

Find matching any: Reset
Dhiman, V
Delgadillo, C.A
Jiang, D
Rekhi, M
Add filter to result:
Authors
Li, L
Jiang, D
Campos, R.P
Lu, Z
Tian, L.F
Archer, J.K
Delgadillo, C.A
Shen, F
Evers, B
Rekhi, M
Hettiarachchi, G
Welch, S
Fritz, A
Alderman, P.D
Poland, J
Barai, K
Ewanik, C
Dhiman, V
Zhang, Y
Hodeghatta, U.R
Zhang, Y
Hodeghatta, U.R
Dhiman, V
Barai, K
Trang, T
Topics
Proximal Sensing in Precision Agriculture
Standards & Data Stewardship
Geospatial Data
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Data Analytics for Production Ag
Type
Oral
Poster
Year
2014
2016
2022
2024
Home » Authors » Results

Authors

Filter results5 paper(s) found.

1. Field-Based High-Throughput Phenotyping Approach For Soybean Plant Improvement

The continued development of new, high yielding cultivars needed to meet the world’s growing food demands will be aided by improving the technology to rapidly phenotype potential cultivars. High-throughput phenotyping (HTP) is essential to maximize the greatest value of genetics analysis and to better understand the plant biology and physiology in view of a “Feed the World in 2050” theme. Field-based high-throughput phenotyping platform... L. Li, D. Jiang, R.P. Campos, Z. Lu, L.F. Tian

2. Key Data Ownership, Privacy and Protection Issues and Strategies for the International Precision Agriculture Industry

Precision agriculture companies seek to leverage technology to process greater volumes of data, greater varieties of data, and at a velocity unfathomable to most. The promises of boundless benefits are coupled with risks associated with data ownership, stewardship and privacy. This paper presents some risks related to the management of farm data, in general, as well as those unique to operating in the international arena.  Examples of U.S. and international laws related to data protection... J.K. Archer, C.A. Delgadillo, F. Shen

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. Airborne Spectral Detection of Leaf Chlorophyll Concentration in Wild Blueberries

Leaf chlorophyll concentration (LCC) detection is crucial for monitoring crop physiological status, assessing the overall health of crops, and estimating their photosynthetic potential. Fast, non-destructive, and spatially extensive monitoring of LCC in crops is critical for accurately diagnosing and assessing crop health in large commercial fields. Advancements in hyperspectral remote sensing offer non-destructive and spatially extensive alternatives for monitoring plant parameters such as LCC.... K. Barai, C. Ewanik, V. Dhiman, Y. Zhang, U.R. Hodeghatta

5. Predicting Water Potentials of Wild Blueberries During Drought Treatment Using Hyperspectral Sensor and Machine Learning

Detecting water stress on crops early and accurately is crucial to minimize its impact. This study aims to measure water stress in wild blueberry crops non-destructively by analyzing proximal hyperspectral data. The data collection took place in the summer growing season of 2022. A drought experiment was conducted on wild blueberries in the randomized block design in the greenhouse, incorporating various genotypes and irrigation treatments. Hyperspectral data ( spectral range: 400-1000 nm) using... Y. Zhang, U.R. Hodeghatta, V. Dhiman, K. Barai, T. Trang