Proceedings

Find matching any: Reset
G, S
Romani, M
Carroll, S
Paindavoine, M
Dhiman, V
Add filter to result:
Authors
Cointault, F
Hijazi, B
Dubois, J
Vangeyte, J
Paindavoine, M
Parajulee, M
Neupane, D
Wang, C
Carroll, S
Shrestha, R
Cordero, E
Sacco, D
Moretti, B
Miniotti, E.F
Tenni, D
Beltarre, G
Romani, M
Grignani, C
G, S
Biradar, D.P
Desai, B.L
Patil, V.C
Patil, P
Nargund, V.B
Desai, V
John, W
Channangi, S.M
Tulasigeri, V
Barai, K
Ewanik, C
Dhiman, V
Zhang, Y
Hodeghatta, U.R
Zhang, Y
Hodeghatta, U.R
Dhiman, V
Barai, K
Trang, T
Topics
Engineering Technologies and Advances
Precision Nutrient Management
In-Season Nitrogen Management
Applications of Unmanned Aerial Systems
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Data Analytics for Production Ag
Type
Oral
Poster
Year
2010
2018
2024
Home » Authors » Results

Authors

Filter results6 paper(s) found.

1. New Power-leds Based Illumination System For Fertilizer Granule Motion Estimation

Environmental problems have become more and more pressing in the past twenty years particularly with the fertilization operation, one main contributor to environmental imbalance. The understanding of the global centrifugal spreading process, most commonly used in Europe, can contribute to provide essential information about fertiliser granule deposition on the soil. This last one can be predicted using a ballistic flight model and several fertilizer characteristic’s determination... F. Cointault, B. Hijazi, J. Dubois, J. Vangeyte, M. Paindavoine

2. Effect Of Nitrogen Application Rate On Soil Residual N And Cotton Yield

A long-term study was conducted on nitrogen application rate and its impact on soil residual nitrogen and cotton (FM960B2RF) lint yield under a drip irrigation production system near Plainview, Texas. The experiment was a randomized complete block design with five nitrogen application rates (0, 56, 112, 168 and 224 kg per ha) and five replications. The soil nitrogen treatment was applied as side dressing. Cotton yield, leaf N, seed N, soil residual nitrate, amount of irrigation, and rainfall data... M. Parajulee, D. Neupane, C. Wang, S. Carroll, R. Shrestha

3. Deriving Fertiliser VRA Calibration Based on Ground Sensing Data from Specific Field Experiments

Nitrogen (N) fertilisation affects both rice yield and quality. In order to improve grain yield while limiting N losses, providing N fertilisers during the critical growth stages is essential. NDRE is considered a reliable crop N status indicator, suitable to drive topdressing N fertilisation in rice. A multi-year experiment on different rice varieties (Gladio, Centauro, and Carnaroli) was conducted between 2011 and 2017 in Castello d’Agogna (PV), northwest Italy, with the aim of i) establishing... E. Cordero, D. Sacco, B. Moretti, E.F. Miniotti, D. Tenni, G. Beltarre, M. Romani, C. Grignani

4. Prototype Unmanned Aerial Sprayer for Plant Protection in Agricultural and Horticultural Crops

Aerial application of pesticides has the potential to reduce the amount of pesticides required as chemicals are applied where needed. A prototype Unmanned Aerial Sprayer with a payload of 20 kg; a spraying rate of 6 liters per minute; a spraying swathe of 3 meters, coverage rate of 2 to 4 meters per second and 10 minutes of flight time was built using state of the art technologies. The project is a joint development by University of Agricultural Sciences, Dharwad, KLE Technological University,... S. G, D.P. Biradar, B.L. Desai, V.C. Patil, P. Patil, V.B. Nargund, V. Desai, W. John, S.M. Channangi, V. Tulasigeri

5. 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

6. 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